{"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 360-feature input with 131 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-0\nComponents:\n - input (input) params={\"shape\":[1,360]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,360]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":360,\"outFeatures\":92}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":92,\"outFeatures\":968}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":968,\"outFeatures\":415}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":415,\"outFeatures\":174}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":174,\"outFeatures\":277}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":277,\"outFeatures\":131}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1458-dim input: encode down to a 137-dim bottleneck and decode back to 1458. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1\nComponents:\n - input (input) params={\"shape\":[1,1458]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1458]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1458,\"outFeatures\":751}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":751,\"outFeatures\":137}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":137,\"outFeatures\":751}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":751,\"outFeatures\":1458}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x34x34 image with 18 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2\nComponents:\n - input (input) params={\"shape\":[1,3,34,34]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,34,34]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":34,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":34,\"outChannels\":8,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":8,\"outChannels\":29,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":29,\"outFeatures\":18}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 477-token sequences with 81 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-3\nComponents:\n - input (input) params={\"shape\":[1,477]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,477]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":14273,\"embeddingDim\":456}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":456,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":456,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":456,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":456,\"outFeatures\":81}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 427-token sequences with 33 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-4\nComponents:\n - input (input) params={\"shape\":[1,427]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,427]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":9762,\"embeddingDim\":184}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":184,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[184]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":184,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[184]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":184,\"outFeatures\":33}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 2917-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-6\nComponents:\n - input (input) params={\"shape\":[1,218]}\n - fc1 (linear) params={\"inFeatures\":218,\"outFeatures\":2917}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2917,\"outFeatures\":2917}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2917,\"outFeatures\":2917}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":2917,\"outFeatures\":45}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":218,\"outFeatures\":126}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":126,\"outFeatures\":126}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":126,\"outFeatures\":126}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":126,\"outFeatures\":45}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 129-feature, 87-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-7\nComponents:\n - input (input) params={\"shape\":[1,129]}\n - fc1 (linear) params={\"inFeatures\":129,\"outFeatures\":380}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":380,\"outFeatures\":200}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":200,\"outFeatures\":292}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":292,\"outFeatures\":342}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":342,\"outFeatures\":87}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":380}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":200}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":292}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":342}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 108-feature user input and a 187-feature item input, each through its own 2-layer MLP tower ending at width 439, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-8\nComponents:\n - user_input (input) params={\"shape\":[1,108]}\n - item_input (input) params={\"shape\":[1,187]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,108]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,187]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":108,\"outFeatures\":439}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":439,\"outFeatures\":439}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":187,\"outFeatures\":439}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":439,\"outFeatures\":439}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":878,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (49-feature input, 10 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-9\nComponents:\n - input (input) params={\"shape\":[1,49]}\n - fc1 (linear) params={\"inFeatures\":49,\"outFeatures\":15}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":15,\"outFeatures\":15}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":15,\"outFeatures\":10}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":49,\"outFeatures\":1281}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1281,\"outFeatures\":1281}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1281,\"outFeatures\":10}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 367-feature input with 140 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-10\nComponents:\n - input (input) params={\"shape\":[1,367]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,367]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":367,\"outFeatures\":130}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":130,\"outFeatures\":913}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":913,\"outFeatures\":726}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":726,\"outFeatures\":389}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":389,\"outFeatures\":425}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":425,\"outFeatures\":393}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":393,\"outFeatures\":140}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1396-dim input: encode down to a 176-dim bottleneck and decode back to 1396. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-11\nComponents:\n - input (input) params={\"shape\":[1,1396]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1396]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1396,\"outFeatures\":806}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":806,\"outFeatures\":176}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":176,\"outFeatures\":806}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":806,\"outFeatures\":1396}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x62x62 image with 7 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-12\nComponents:\n - input (input) params={\"shape\":[1,3,62,62]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,62,62]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":31,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":31,\"outChannels\":44,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":44,\"outChannels\":64,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":64,\"outChannels\":28,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":28,\"outFeatures\":7}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 101-token sequences with 10 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-13\nComponents:\n - input (input) params={\"shape\":[1,101]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,101]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":21817,\"embeddingDim\":18}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":18,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":18,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":18,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":18,\"outFeatures\":10}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 445-token sequences with 99 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-14\nComponents:\n - input (input) params={\"shape\":[1,445]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,445]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":13664,\"embeddingDim\":156}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":156,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[156]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":156,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[156]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":156,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[156]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":156,\"outFeatures\":99}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (502) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-15\nComponents:\n - input (input) params={\"shape\":[1,464]}\n - embed (embedding) params={\"numEmbeddings\":49641,\"embeddingDim\":502}\n - attn (multiHeadAttention) params={\"embedDim\":502,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":502,\"outFeatures\":84}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 2926-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-16\nComponents:\n - input (input) params={\"shape\":[1,41]}\n - fc1 (linear) params={\"inFeatures\":41,\"outFeatures\":2926}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2926,\"outFeatures\":2926}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2926,\"outFeatures\":2926}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":2926,\"outFeatures\":22}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":41,\"outFeatures\":283}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":283,\"outFeatures\":283}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":283,\"outFeatures\":283}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":283,\"outFeatures\":22}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 200-feature, 86-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-17\nComponents:\n - input (input) params={\"shape\":[1,200]}\n - fc1 (linear) params={\"inFeatures\":200,\"outFeatures\":386}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":386,\"outFeatures\":282}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":282,\"outFeatures\":86}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":386}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":282}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 139-feature user input and a 236-feature item input, each through its own 2-layer MLP tower ending at width 494, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-18\nComponents:\n - user_input (input) params={\"shape\":[1,139]}\n - item_input (input) params={\"shape\":[1,236]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,139]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,236]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":139,\"outFeatures\":494}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":494,\"outFeatures\":494}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":236,\"outFeatures\":494}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":494,\"outFeatures\":494}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":988,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 269-feature input with 58 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-20\nComponents:\n - input (input) params={\"shape\":[1,269]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,269]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":269,\"outFeatures\":699}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":699,\"outFeatures\":610}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":610,\"outFeatures\":362}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":362,\"outFeatures\":610}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":610,\"outFeatures\":431}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":431,\"outFeatures\":58}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1354-dim input: encode down to a 160-dim bottleneck and decode back to 1354. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-21\nComponents:\n - input (input) params={\"shape\":[1,1354]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1354]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1354,\"outFeatures\":790}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":790,\"outFeatures\":160}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":160,\"outFeatures\":790}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":790,\"outFeatures\":1354}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x44x44 image with 23 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-22\nComponents:\n - input (input) params={\"shape\":[1,3,44,44]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,44,44]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":43,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":43,\"outChannels\":24,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":24,\"outChannels\":62,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":62,\"outChannels\":37,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":37,\"outFeatures\":23}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 432-token sequences with 15 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-23\nComponents:\n - input (input) params={\"shape\":[1,432]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,432]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":28261,\"embeddingDim\":116}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":116,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":116,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":116,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":116,\"outFeatures\":15}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 229-token sequences with 41 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-24\nComponents:\n - input (input) params={\"shape\":[1,229]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,229]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":11849,\"embeddingDim\":80}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":80,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[80]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":80,\"outFeatures\":41}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (102) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-25\nComponents:\n - input (input) params={\"shape\":[1,383]}\n - embed (embedding) params={\"numEmbeddings\":44483,\"embeddingDim\":102}\n - attn (multiHeadAttention) params={\"embedDim\":102,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":102,\"outFeatures\":29}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 3342-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-26\nComponents:\n - input (input) params={\"shape\":[1,125]}\n - fc1 (linear) params={\"inFeatures\":125,\"outFeatures\":3342}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3342,\"outFeatures\":3342}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":3342,\"outFeatures\":36}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":125,\"outFeatures\":156}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":156,\"outFeatures\":156}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":156,\"outFeatures\":36}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 220-feature, 63-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-27\nComponents:\n - input (input) params={\"shape\":[1,220]}\n - fc1 (linear) params={\"inFeatures\":220,\"outFeatures\":198}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":198,\"outFeatures\":502}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":502,\"outFeatures\":360}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":360,\"outFeatures\":136}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":136,\"outFeatures\":63}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":198}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":502}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":360}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":136}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 49-feature user input and a 83-feature item input, each through its own 2-layer MLP tower ending at width 213, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-28\nComponents:\n - user_input (input) params={\"shape\":[1,49]}\n - item_input (input) params={\"shape\":[1,83]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,49]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,83]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":49,\"outFeatures\":213}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":213,\"outFeatures\":213}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":83,\"outFeatures\":213}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":213,\"outFeatures\":213}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":426,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (24-feature input, 27 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-29\nComponents:\n - input (input) params={\"shape\":[1,24]}\n - fc1 (linear) params={\"inFeatures\":24,\"outFeatures\":13}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":13,\"outFeatures\":13}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":13,\"outFeatures\":27}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":24,\"outFeatures\":870}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":870,\"outFeatures\":870}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":870,\"outFeatures\":27}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 97-feature input with 160 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-30\nComponents:\n - input (input) params={\"shape\":[1,97]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,97]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":97,\"outFeatures\":977}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":977,\"outFeatures\":138}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":138,\"outFeatures\":510}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":510,\"outFeatures\":160}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1371-dim input: encode down to a 90-dim bottleneck and decode back to 1371. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-31\nComponents:\n - input (input) params={\"shape\":[1,1371]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1371]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1371,\"outFeatures\":812}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":812,\"outFeatures\":90}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":90,\"outFeatures\":812}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":812,\"outFeatures\":1371}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x64x64 image with 3 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-32\nComponents:\n - input (input) params={\"shape\":[1,3,64,64]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,64,64]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":23,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":23,\"outChannels\":20,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":20,\"outChannels\":40,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":40,\"outFeatures\":3}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 106-token sequences with 23 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-33\nComponents:\n - input (input) params={\"shape\":[1,106]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,106]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":31624,\"embeddingDim\":112}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":112,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":112,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":112,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":112,\"outFeatures\":23}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 448-token sequences with 81 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-34\nComponents:\n - input (input) params={\"shape\":[1,448]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,448]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":39493,\"embeddingDim\":128}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":128,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[128]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":128,\"outFeatures\":81}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (456) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-35\nComponents:\n - input (input) params={\"shape\":[1,115]}\n - embed (embedding) params={\"numEmbeddings\":30610,\"embeddingDim\":456}\n - attn (multiHeadAttention) params={\"embedDim\":456,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":456,\"outFeatures\":94}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":8}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 2259-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-36\nComponents:\n - input (input) params={\"shape\":[1,152]}\n - fc1 (linear) params={\"inFeatures\":152,\"outFeatures\":2259}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2259,\"outFeatures\":2259}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2259,\"outFeatures\":2259}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":2259,\"outFeatures\":20}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":152,\"outFeatures\":137}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":137,\"outFeatures\":137}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":137,\"outFeatures\":137}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":137,\"outFeatures\":20}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 59-feature, 97-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-37\nComponents:\n - input (input) params={\"shape\":[1,59]}\n - fc1 (linear) params={\"inFeatures\":59,\"outFeatures\":450}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":450,\"outFeatures\":237}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":237,\"outFeatures\":152}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":152,\"outFeatures\":118}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":118,\"outFeatures\":97}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":450}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":237}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":152}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":118}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 137-feature user input and a 49-feature item input, each through its own 2-layer MLP tower ending at width 37, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-38\nComponents:\n - user_input (input) params={\"shape\":[1,137]}\n - item_input (input) params={\"shape\":[1,49]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,137]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,49]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":137,\"outFeatures\":37}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":37,\"outFeatures\":37}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":49,\"outFeatures\":37}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":37,\"outFeatures\":37}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":74,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (128-feature input, 22 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-39\nComponents:\n - input (input) params={\"shape\":[1,128]}\n - fc1 (linear) params={\"inFeatures\":128,\"outFeatures\":24}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":24,\"outFeatures\":24}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":24,\"outFeatures\":22}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":128,\"outFeatures\":980}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":980,\"outFeatures\":980}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":980,\"outFeatures\":22}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 463-feature input with 64 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-40\nComponents:\n - input (input) params={\"shape\":[1,463]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,463]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":463,\"outFeatures\":452}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":452,\"outFeatures\":426}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":426,\"outFeatures\":64}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1973-dim input: encode down to a 222-dim bottleneck and decode back to 1973. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-41\nComponents:\n - input (input) params={\"shape\":[1,1973]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1973]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1973,\"outFeatures\":614}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":614,\"outFeatures\":222}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":222,\"outFeatures\":614}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":614,\"outFeatures\":1973}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x42x42 image with 53 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-42\nComponents:\n - input (input) params={\"shape\":[1,3,42,42]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,42,42]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":54,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":54,\"outChannels\":62,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":62,\"outChannels\":14,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":14,\"outChannels\":42,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":42,\"outFeatures\":53}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 358-token sequences with 87 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-43\nComponents:\n - input (input) params={\"shape\":[1,358]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,358]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":45415,\"embeddingDim\":184}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":184,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":184,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":184,\"outFeatures\":87}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 256-token sequences with 9 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-44\nComponents:\n - input (input) params={\"shape\":[1,256]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,256]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":12157,\"embeddingDim\":384}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":384,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[384]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":384,\"outFeatures\":9}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (408) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-45\nComponents:\n - input (input) params={\"shape\":[1,132]}\n - embed (embedding) params={\"numEmbeddings\":19058,\"embeddingDim\":408}\n - attn (multiHeadAttention) params={\"embedDim\":408,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":408,\"outFeatures\":77}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":8}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3785-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-46\nComponents:\n - input (input) params={\"shape\":[1,202]}\n - fc1 (linear) params={\"inFeatures\":202,\"outFeatures\":3785}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3785,\"outFeatures\":3785}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3785,\"outFeatures\":3785}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3785,\"outFeatures\":3785}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3785,\"outFeatures\":3}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":202,\"outFeatures\":128}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":128,\"outFeatures\":128}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":128,\"outFeatures\":128}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":128,\"outFeatures\":128}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":128,\"outFeatures\":3}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 107-feature, 34-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-47\nComponents:\n - input (input) params={\"shape\":[1,107]}\n - fc1 (linear) params={\"inFeatures\":107,\"outFeatures\":415}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":415,\"outFeatures\":291}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":291,\"outFeatures\":375}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":375,\"outFeatures\":34}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":415}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":291}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":375}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 218-feature user input and a 212-feature item input, each through its own 2-layer MLP tower ending at width 288, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-48\nComponents:\n - user_input (input) params={\"shape\":[1,218]}\n - item_input (input) params={\"shape\":[1,212]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,218]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,212]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":218,\"outFeatures\":288}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":288,\"outFeatures\":288}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":212,\"outFeatures\":288}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":288,\"outFeatures\":288}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":576,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (49-feature input, 36 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-49\nComponents:\n - input (input) params={\"shape\":[1,49]}\n - fc1 (linear) params={\"inFeatures\":49,\"outFeatures\":21}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":21,\"outFeatures\":21}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":21,\"outFeatures\":36}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":49,\"outFeatures\":736}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":736,\"outFeatures\":736}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":736,\"outFeatures\":36}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 433-feature input with 82 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-50\nComponents:\n - input (input) params={\"shape\":[1,433]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,433]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":433,\"outFeatures\":365}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":365,\"outFeatures\":242}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":242,\"outFeatures\":624}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":624,\"outFeatures\":774}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":774,\"outFeatures\":82}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 254-dim input: encode down to a 53-dim bottleneck and decode back to 254. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-51\nComponents:\n - input (input) params={\"shape\":[1,254]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,254]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":254,\"outFeatures\":768}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":768,\"outFeatures\":53}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":53,\"outFeatures\":768}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":768,\"outFeatures\":254}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x36x36 image with 80 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-52\nComponents:\n - input (input) params={\"shape\":[1,3,36,36]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,36,36]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":25,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":25,\"outChannels\":47,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":47,\"outFeatures\":80}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 300-token sequences with 44 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-53\nComponents:\n - input (input) params={\"shape\":[1,300]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,300]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":34357,\"embeddingDim\":36}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":36,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":36,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":36,\"outFeatures\":44}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 42-token sequences with 47 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-54\nComponents:\n - input (input) params={\"shape\":[1,42]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,42]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":27016,\"embeddingDim\":160}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":160,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[160]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":160,\"outFeatures\":47}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (380) is not divisible by numHeads (7). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-55\nComponents:\n - input (input) params={\"shape\":[1,213]}\n - embed (embedding) params={\"numEmbeddings\":9646,\"embeddingDim\":380}\n - attn (multiHeadAttention) params={\"embedDim\":380,\"numHeads\":7}\n - head (linear) params={\"inFeatures\":380,\"outFeatures\":87}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":4}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 3706-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-56\nComponents:\n - input (input) params={\"shape\":[1,239]}\n - fc1 (linear) params={\"inFeatures\":239,\"outFeatures\":3706}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3706,\"outFeatures\":3706}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3706,\"outFeatures\":3706}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":3706,\"outFeatures\":6}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":239,\"outFeatures\":208}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":208,\"outFeatures\":208}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":208,\"outFeatures\":208}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":208,\"outFeatures\":6}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 185-feature, 12-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-57\nComponents:\n - input (input) params={\"shape\":[1,185]}\n - fc1 (linear) params={\"inFeatures\":185,\"outFeatures\":469}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":469,\"outFeatures\":435}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":435,\"outFeatures\":32}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":32,\"outFeatures\":12}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":469}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":435}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":32}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 61-feature user input and a 21-feature item input, each through its own 2-layer MLP tower ending at width 371, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-58\nComponents:\n - user_input (input) params={\"shape\":[1,61]}\n - item_input (input) params={\"shape\":[1,21]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,61]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,21]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":61,\"outFeatures\":371}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":371,\"outFeatures\":371}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":21,\"outFeatures\":371}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":371,\"outFeatures\":371}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":742,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (77-feature input, 29 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-59\nComponents:\n - input (input) params={\"shape\":[1,77]}\n - fc1 (linear) params={\"inFeatures\":77,\"outFeatures\":18}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":18,\"outFeatures\":18}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":18,\"outFeatures\":29}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":77,\"outFeatures\":710}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":710,\"outFeatures\":710}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":710,\"outFeatures\":29}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 214-feature input with 90 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-60\nComponents:\n - input (input) params={\"shape\":[1,214]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,214]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":214,\"outFeatures\":87}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":87,\"outFeatures\":292}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":292,\"outFeatures\":90}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1464-dim input: encode down to a 19-dim bottleneck and decode back to 1464. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-61\nComponents:\n - input (input) params={\"shape\":[1,1464]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1464]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1464,\"outFeatures\":199}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":199,\"outFeatures\":19}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":19,\"outFeatures\":199}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":199,\"outFeatures\":1464}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x44x44 image with 20 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-62\nComponents:\n - input (input) params={\"shape\":[1,3,44,44]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,44,44]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":8,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":8,\"outChannels\":60,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":60,\"outChannels\":53,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":53,\"outFeatures\":20}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 307-token sequences with 81 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-63\nComponents:\n - input (input) params={\"shape\":[1,307]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,307]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":23858,\"embeddingDim\":472}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":472,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":472,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":472,\"outFeatures\":81}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 231-token sequences with 41 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-64\nComponents:\n - input (input) params={\"shape\":[1,231]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,231]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":47585,\"embeddingDim\":352}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":352,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[352]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":352,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[352]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":352,\"outFeatures\":41}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 3419-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-66\nComponents:\n - input (input) params={\"shape\":[1,157]}\n - fc1 (linear) params={\"inFeatures\":157,\"outFeatures\":3419}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3419,\"outFeatures\":3419}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":3419,\"outFeatures\":37}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":157,\"outFeatures\":267}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":267,\"outFeatures\":267}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":267,\"outFeatures\":37}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 120-feature, 36-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-67\nComponents:\n - input (input) params={\"shape\":[1,120]}\n - fc1 (linear) params={\"inFeatures\":120,\"outFeatures\":384}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":384,\"outFeatures\":232}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":232,\"outFeatures\":183}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":183,\"outFeatures\":36}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":384}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":232}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":183}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 50-feature user input and a 25-feature item input, each through its own 2-layer MLP tower ending at width 165, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-68\nComponents:\n - user_input (input) params={\"shape\":[1,50]}\n - item_input (input) params={\"shape\":[1,25]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,50]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,25]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":50,\"outFeatures\":165}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":165,\"outFeatures\":165}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":25,\"outFeatures\":165}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":165,\"outFeatures\":165}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":330,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (38-feature input, 18 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-69\nComponents:\n - input (input) params={\"shape\":[1,38]}\n - fc1 (linear) params={\"inFeatures\":38,\"outFeatures\":5}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":5,\"outFeatures\":5}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":5,\"outFeatures\":18}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":38,\"outFeatures\":939}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":939,\"outFeatures\":939}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":939,\"outFeatures\":18}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 89-feature input with 100 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-70\nComponents:\n - input (input) params={\"shape\":[1,89]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,89]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":89,\"outFeatures\":919}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":919,\"outFeatures\":881}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":881,\"outFeatures\":664}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":664,\"outFeatures\":112}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":112,\"outFeatures\":100}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1854-dim input: encode down to a 195-dim bottleneck and decode back to 1854. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-71\nComponents:\n - input (input) params={\"shape\":[1,1854]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1854]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1854,\"outFeatures\":914}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":914,\"outFeatures\":195}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":195,\"outFeatures\":914}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":914,\"outFeatures\":1854}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x29x29 image with 70 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-72\nComponents:\n - input (input) params={\"shape\":[1,3,29,29]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,29,29]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":37,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":37,\"outChannels\":55,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":55,\"outChannels\":16,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":16,\"outChannels\":44,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":44,\"outFeatures\":70}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 110-token sequences with 50 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-73\nComponents:\n - input (input) params={\"shape\":[1,110]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,110]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":21052,\"embeddingDim\":48}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":48,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":48,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":48,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":48,\"outFeatures\":50}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 396-token sequences with 86 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-74\nComponents:\n - input (input) params={\"shape\":[1,396]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,396]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":49491,\"embeddingDim\":96}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":96,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[96]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":96,\"outFeatures\":86}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 2649-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-76\nComponents:\n - input (input) params={\"shape\":[1,137]}\n - fc1 (linear) params={\"inFeatures\":137,\"outFeatures\":2649}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2649,\"outFeatures\":2649}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2649,\"outFeatures\":2649}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":2649,\"outFeatures\":26}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":137,\"outFeatures\":116}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":116,\"outFeatures\":116}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":116,\"outFeatures\":116}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":116,\"outFeatures\":26}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 142-feature, 29-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-77\nComponents:\n - input (input) params={\"shape\":[1,142]}\n - fc1 (linear) params={\"inFeatures\":142,\"outFeatures\":488}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":488,\"outFeatures\":267}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":267,\"outFeatures\":476}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":476,\"outFeatures\":446}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":446,\"outFeatures\":393}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":393,\"outFeatures\":29}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":488}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":267}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":476}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":446}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":393}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 108-feature user input and a 160-feature item input, each through its own 2-layer MLP tower ending at width 83, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-78\nComponents:\n - user_input (input) params={\"shape\":[1,108]}\n - item_input (input) params={\"shape\":[1,160]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,108]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,160]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":108,\"outFeatures\":83}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":83,\"outFeatures\":83}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":160,\"outFeatures\":83}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":83,\"outFeatures\":83}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":166,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (16-feature input, 7 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-79\nComponents:\n - input (input) params={\"shape\":[1,16]}\n - fc1 (linear) params={\"inFeatures\":16,\"outFeatures\":14}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":14,\"outFeatures\":14}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":14,\"outFeatures\":7}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":16,\"outFeatures\":859}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":859,\"outFeatures\":859}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":859,\"outFeatures\":7}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 319-feature input with 13 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-80\nComponents:\n - input (input) params={\"shape\":[1,319]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,319]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":319,\"outFeatures\":736}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":736,\"outFeatures\":34}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":34,\"outFeatures\":242}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":242,\"outFeatures\":930}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":930,\"outFeatures\":124}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":124,\"outFeatures\":914}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":914,\"outFeatures\":13}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1699-dim input: encode down to a 33-dim bottleneck and decode back to 1699. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-81\nComponents:\n - input (input) params={\"shape\":[1,1699]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1699]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1699,\"outFeatures\":383}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":383,\"outFeatures\":33}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":33,\"outFeatures\":383}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":383,\"outFeatures\":1699}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x33x33 image with 33 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-82\nComponents:\n - input (input) params={\"shape\":[1,3,33,33]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,33,33]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":46,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":46,\"outChannels\":49,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":49,\"outChannels\":30,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":30,\"outFeatures\":33}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 236-token sequences with 21 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-83\nComponents:\n - input (input) params={\"shape\":[1,236]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,236]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":23156,\"embeddingDim\":220}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":220,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":220,\"outFeatures\":21}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 499-token sequences with 29 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-84\nComponents:\n - input (input) params={\"shape\":[1,499]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,499]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":17015,\"embeddingDim\":180}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":180,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[180]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":180,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[180]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":180,\"outFeatures\":29}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (144) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-85\nComponents:\n - input (input) params={\"shape\":[1,130]}\n - embed (embedding) params={\"numEmbeddings\":47768,\"embeddingDim\":144}\n - attn (multiHeadAttention) params={\"embedDim\":144,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":144,\"outFeatures\":82}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":16}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 1864-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-86\nComponents:\n - input (input) params={\"shape\":[1,45]}\n - fc1 (linear) params={\"inFeatures\":45,\"outFeatures\":1864}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":1864,\"outFeatures\":1864}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":1864,\"outFeatures\":3}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":45,\"outFeatures\":312}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":312,\"outFeatures\":312}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":312,\"outFeatures\":3}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 103-feature, 2-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-87\nComponents:\n - input (input) params={\"shape\":[1,103]}\n - fc1 (linear) params={\"inFeatures\":103,\"outFeatures\":408}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":408,\"outFeatures\":428}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":428,\"outFeatures\":345}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":345,\"outFeatures\":438}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":438,\"outFeatures\":136}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":136,\"outFeatures\":2}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":408}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":428}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":345}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":438}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":136}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 60-feature user input and a 85-feature item input, each through its own 2-layer MLP tower ending at width 445, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-88\nComponents:\n - user_input (input) params={\"shape\":[1,60]}\n - item_input (input) params={\"shape\":[1,85]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,60]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,85]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":60,\"outFeatures\":445}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":445,\"outFeatures\":445}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":85,\"outFeatures\":445}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":445,\"outFeatures\":445}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":890,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (91-feature input, 6 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-89\nComponents:\n - input (input) params={\"shape\":[1,91]}\n - fc1 (linear) params={\"inFeatures\":91,\"outFeatures\":6}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":6,\"outFeatures\":6}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":6,\"outFeatures\":6}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":91,\"outFeatures\":1046}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1046,\"outFeatures\":1046}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1046,\"outFeatures\":6}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 441-feature input with 57 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-90\nComponents:\n - input (input) params={\"shape\":[1,441]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,441]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":441,\"outFeatures\":1007}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1007,\"outFeatures\":874}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":874,\"outFeatures\":183}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":183,\"outFeatures\":367}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":367,\"outFeatures\":234}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":234,\"outFeatures\":566}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":566,\"outFeatures\":57}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 865-dim input: encode down to a 235-dim bottleneck and decode back to 865. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-91\nComponents:\n - input (input) params={\"shape\":[1,865]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,865]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":865,\"outFeatures\":992}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":992,\"outFeatures\":235}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":235,\"outFeatures\":992}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":992,\"outFeatures\":865}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x57x57 image with 43 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-92\nComponents:\n - input (input) params={\"shape\":[1,3,57,57]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,57,57]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":64,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":64,\"outChannels\":46,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":46,\"outChannels\":56,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":56,\"outChannels\":34,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":34,\"outFeatures\":43}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 489-token sequences with 41 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-93\nComponents:\n - input (input) params={\"shape\":[1,489]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,489]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":22532,\"embeddingDim\":40}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":40,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":40,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":40,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":40,\"outFeatures\":41}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 455-token sequences with 75 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-94\nComponents:\n - input (input) params={\"shape\":[1,455]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,455]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":19074,\"embeddingDim\":256}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":256,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[256]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":256,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[256]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":256,\"outFeatures\":75}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (392) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-95\nComponents:\n - input (input) params={\"shape\":[1,39]}\n - embed (embedding) params={\"numEmbeddings\":12228,\"embeddingDim\":392}\n - attn (multiHeadAttention) params={\"embedDim\":392,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":392,\"outFeatures\":64}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":8}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 2597-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-96\nComponents:\n - input (input) params={\"shape\":[1,83]}\n - fc1 (linear) params={\"inFeatures\":83,\"outFeatures\":2597}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2597,\"outFeatures\":2597}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2597,\"outFeatures\":2597}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":2597,\"outFeatures\":5}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":83,\"outFeatures\":98}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":98,\"outFeatures\":98}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":98,\"outFeatures\":98}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":98,\"outFeatures\":5}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 32-feature, 38-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-97\nComponents:\n - input (input) params={\"shape\":[1,32]}\n - fc1 (linear) params={\"inFeatures\":32,\"outFeatures\":440}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":440,\"outFeatures\":65}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":65,\"outFeatures\":38}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":440}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":65}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 50-feature user input and a 85-feature item input, each through its own 2-layer MLP tower ending at width 490, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-98\nComponents:\n - user_input (input) params={\"shape\":[1,50]}\n - item_input (input) params={\"shape\":[1,85]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,50]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,85]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":50,\"outFeatures\":490}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":490,\"outFeatures\":490}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":85,\"outFeatures\":490}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":490,\"outFeatures\":490}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":980,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (127-feature input, 43 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-99\nComponents:\n - input (input) params={\"shape\":[1,127]}\n - fc1 (linear) params={\"inFeatures\":127,\"outFeatures\":17}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":17,\"outFeatures\":17}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":17,\"outFeatures\":43}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":127,\"outFeatures\":1191}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1191,\"outFeatures\":1191}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1191,\"outFeatures\":43}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 312-feature input with 7 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-100\nComponents:\n - input (input) params={\"shape\":[1,312]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,312]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":312,\"outFeatures\":502}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":502,\"outFeatures\":942}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":942,\"outFeatures\":7}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1199-dim input: encode down to a 211-dim bottleneck and decode back to 1199. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-101\nComponents:\n - input (input) params={\"shape\":[1,1199]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1199]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1199,\"outFeatures\":920}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":920,\"outFeatures\":211}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":211,\"outFeatures\":920}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":920,\"outFeatures\":1199}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x43x43 image with 43 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-102\nComponents:\n - input (input) params={\"shape\":[1,3,43,43]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,43,43]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":20,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":20,\"outChannels\":12,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":12,\"outChannels\":63,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":63,\"outFeatures\":43}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 385-token sequences with 6 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-103\nComponents:\n - input (input) params={\"shape\":[1,385]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,385]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":49989,\"embeddingDim\":136}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":136,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":136,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":136,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":136,\"outFeatures\":6}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 47-token sequences with 26 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-104\nComponents:\n - input (input) params={\"shape\":[1,47]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,47]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":41066,\"embeddingDim\":96}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":96,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[96]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":96,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[96]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":96,\"outFeatures\":26}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 2882-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-106\nComponents:\n - input (input) params={\"shape\":[1,213]}\n - fc1 (linear) params={\"inFeatures\":213,\"outFeatures\":2882}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2882,\"outFeatures\":2882}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2882,\"outFeatures\":2882}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":2882,\"outFeatures\":2882}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":2882,\"outFeatures\":20}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":213,\"outFeatures\":82}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":82,\"outFeatures\":82}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":82,\"outFeatures\":82}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":82,\"outFeatures\":82}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":82,\"outFeatures\":20}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 26-feature, 56-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-107\nComponents:\n - input (input) params={\"shape\":[1,26]}\n - fc1 (linear) params={\"inFeatures\":26,\"outFeatures\":409}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":409,\"outFeatures\":143}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":143,\"outFeatures\":56}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":409}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":143}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 81-feature user input and a 157-feature item input, each through its own 2-layer MLP tower ending at width 100, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-108\nComponents:\n - user_input (input) params={\"shape\":[1,81]}\n - item_input (input) params={\"shape\":[1,157]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,81]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,157]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":81,\"outFeatures\":100}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":100,\"outFeatures\":100}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":157,\"outFeatures\":100}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":100,\"outFeatures\":100}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":200,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (76-feature input, 43 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-109\nComponents:\n - input (input) params={\"shape\":[1,76]}\n - fc1 (linear) params={\"inFeatures\":76,\"outFeatures\":21}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":21,\"outFeatures\":21}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":21,\"outFeatures\":43}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":76,\"outFeatures\":1083}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1083,\"outFeatures\":1083}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1083,\"outFeatures\":43}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 128-feature input with 108 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-110\nComponents:\n - input (input) params={\"shape\":[1,128]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,128]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":128,\"outFeatures\":58}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":58,\"outFeatures\":979}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":979,\"outFeatures\":603}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":603,\"outFeatures\":108}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 2047-dim input: encode down to a 76-dim bottleneck and decode back to 2047. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-111\nComponents:\n - input (input) params={\"shape\":[1,2047]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,2047]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":2047,\"outFeatures\":111}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":111,\"outFeatures\":76}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":76,\"outFeatures\":111}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":111,\"outFeatures\":2047}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x38x38 image with 23 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-112\nComponents:\n - input (input) params={\"shape\":[1,3,38,38]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,38,38]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":24,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":24,\"outChannels\":62,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":62,\"outChannels\":33,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":33,\"outFeatures\":23}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 58-token sequences with 70 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-113\nComponents:\n - input (input) params={\"shape\":[1,58]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,58]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":33337,\"embeddingDim\":110}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":110,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":110,\"outFeatures\":70}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 128-token sequences with 5 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-114\nComponents:\n - input (input) params={\"shape\":[1,128]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,128]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":13705,\"embeddingDim\":656}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":656,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[656]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":656,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[656]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":656,\"outFeatures\":5}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 4043-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-116\nComponents:\n - input (input) params={\"shape\":[1,135]}\n - fc1 (linear) params={\"inFeatures\":135,\"outFeatures\":4043}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":4043,\"outFeatures\":4043}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":4043,\"outFeatures\":4043}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":4043,\"outFeatures\":49}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":135,\"outFeatures\":140}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":140,\"outFeatures\":140}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":140,\"outFeatures\":140}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":140,\"outFeatures\":49}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 195-feature, 92-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-117\nComponents:\n - input (input) params={\"shape\":[1,195]}\n - fc1 (linear) params={\"inFeatures\":195,\"outFeatures\":204}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":204,\"outFeatures\":372}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":372,\"outFeatures\":423}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":423,\"outFeatures\":423}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":423,\"outFeatures\":373}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":373,\"outFeatures\":92}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":204}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":372}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":423}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":423}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":373}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 240-feature user input and a 22-feature item input, each through its own 2-layer MLP tower ending at width 493, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-118\nComponents:\n - user_input (input) params={\"shape\":[1,240]}\n - item_input (input) params={\"shape\":[1,22]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,240]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,22]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":240,\"outFeatures\":493}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":493,\"outFeatures\":493}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":22,\"outFeatures\":493}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":493,\"outFeatures\":493}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":986,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (64-feature input, 48 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-119\nComponents:\n - input (input) params={\"shape\":[1,64]}\n - fc1 (linear) params={\"inFeatures\":64,\"outFeatures\":20}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":20,\"outFeatures\":20}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":20,\"outFeatures\":48}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":64,\"outFeatures\":1011}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1011,\"outFeatures\":1011}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1011,\"outFeatures\":48}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 72-feature input with 48 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-120\nComponents:\n - input (input) params={\"shape\":[1,72]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,72]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":72,\"outFeatures\":864}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":864,\"outFeatures\":228}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":228,\"outFeatures\":677}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":677,\"outFeatures\":171}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":171,\"outFeatures\":541}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":541,\"outFeatures\":110}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":110,\"outFeatures\":48}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 501-dim input: encode down to a 77-dim bottleneck and decode back to 501. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-121\nComponents:\n - input (input) params={\"shape\":[1,501]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,501]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":501,\"outFeatures\":698}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":698,\"outFeatures\":77}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":77,\"outFeatures\":698}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":698,\"outFeatures\":501}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x54x54 image with 73 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-122\nComponents:\n - input (input) params={\"shape\":[1,3,54,54]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,54,54]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":31,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":31,\"outChannels\":20,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":20,\"outFeatures\":73}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 446-token sequences with 20 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-123\nComponents:\n - input (input) params={\"shape\":[1,446]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,446]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":34295,\"embeddingDim\":78}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":78,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":78,\"outFeatures\":20}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 353-token sequences with 2 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-124\nComponents:\n - input (input) params={\"shape\":[1,353]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,353]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":38894,\"embeddingDim\":288}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":288,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[288]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":288,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[288]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":288,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[288]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":288,\"outFeatures\":2}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 3345-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-126\nComponents:\n - input (input) params={\"shape\":[1,47]}\n - fc1 (linear) params={\"inFeatures\":47,\"outFeatures\":3345}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3345,\"outFeatures\":3345}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3345,\"outFeatures\":3345}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":3345,\"outFeatures\":35}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":47,\"outFeatures\":231}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":231,\"outFeatures\":231}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":231,\"outFeatures\":231}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":231,\"outFeatures\":35}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 105-feature, 3-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-127\nComponents:\n - input (input) params={\"shape\":[1,105]}\n - fc1 (linear) params={\"inFeatures\":105,\"outFeatures\":105}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":105,\"outFeatures\":247}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":247,\"outFeatures\":75}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":75,\"outFeatures\":65}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":65,\"outFeatures\":102}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":102,\"outFeatures\":3}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":105}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":247}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":75}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":65}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":102}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 152-feature user input and a 138-feature item input, each through its own 2-layer MLP tower ending at width 451, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-128\nComponents:\n - user_input (input) params={\"shape\":[1,152]}\n - item_input (input) params={\"shape\":[1,138]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,152]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,138]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":152,\"outFeatures\":451}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":451,\"outFeatures\":451}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":138,\"outFeatures\":451}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":451,\"outFeatures\":451}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":902,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (126-feature input, 19 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-129\nComponents:\n - input (input) params={\"shape\":[1,126]}\n - fc1 (linear) params={\"inFeatures\":126,\"outFeatures\":21}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":21,\"outFeatures\":21}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":21,\"outFeatures\":19}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":126,\"outFeatures\":1178}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1178,\"outFeatures\":1178}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1178,\"outFeatures\":19}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 111-feature input with 55 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-130\nComponents:\n - input (input) params={\"shape\":[1,111]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,111]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":111,\"outFeatures\":477}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":477,\"outFeatures\":925}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":925,\"outFeatures\":193}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":193,\"outFeatures\":425}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":425,\"outFeatures\":957}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":957,\"outFeatures\":655}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":655,\"outFeatures\":55}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 303-dim input: encode down to a 120-dim bottleneck and decode back to 303. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-131\nComponents:\n - input (input) params={\"shape\":[1,303]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,303]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":303,\"outFeatures\":973}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":973,\"outFeatures\":120}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":120,\"outFeatures\":973}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":973,\"outFeatures\":303}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x44x44 image with 32 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-132\nComponents:\n - input (input) params={\"shape\":[1,3,44,44]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,44,44]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":37,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":37,\"outChannels\":61,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":61,\"outChannels\":38,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":38,\"outChannels\":20,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":20,\"outFeatures\":32}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 285-token sequences with 34 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-133\nComponents:\n - input (input) params={\"shape\":[1,285]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,285]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":19088,\"embeddingDim\":82}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":82,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":82,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":82,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":82,\"outFeatures\":34}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 512-token sequences with 90 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-134\nComponents:\n - input (input) params={\"shape\":[1,512]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,512]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":23219,\"embeddingDim\":352}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":352,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[352]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":352,\"outFeatures\":90}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 2906-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-136\nComponents:\n - input (input) params={\"shape\":[1,240]}\n - fc1 (linear) params={\"inFeatures\":240,\"outFeatures\":2906}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2906,\"outFeatures\":2906}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":2906,\"outFeatures\":42}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":240,\"outFeatures\":359}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":359,\"outFeatures\":359}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":359,\"outFeatures\":42}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 122-feature, 98-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-137\nComponents:\n - input (input) params={\"shape\":[1,122]}\n - fc1 (linear) params={\"inFeatures\":122,\"outFeatures\":169}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":169,\"outFeatures\":200}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":200,\"outFeatures\":98}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":169}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":200}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 232-feature user input and a 254-feature item input, each through its own 2-layer MLP tower ending at width 307, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-138\nComponents:\n - user_input (input) params={\"shape\":[1,232]}\n - item_input (input) params={\"shape\":[1,254]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,232]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,254]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":232,\"outFeatures\":307}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":307,\"outFeatures\":307}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":254,\"outFeatures\":307}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":307,\"outFeatures\":307}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":614,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (114-feature input, 22 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-139\nComponents:\n - input (input) params={\"shape\":[1,114]}\n - fc1 (linear) params={\"inFeatures\":114,\"outFeatures\":11}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":11,\"outFeatures\":11}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":11,\"outFeatures\":22}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":114,\"outFeatures\":910}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":910,\"outFeatures\":910}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":910,\"outFeatures\":22}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 453-feature input with 71 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-140\nComponents:\n - input (input) params={\"shape\":[1,453]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,453]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":453,\"outFeatures\":860}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":860,\"outFeatures\":723}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":723,\"outFeatures\":465}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":465,\"outFeatures\":71}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 170-dim input: encode down to a 224-dim bottleneck and decode back to 170. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-141\nComponents:\n - input (input) params={\"shape\":[1,170]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,170]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":170,\"outFeatures\":637}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":637,\"outFeatures\":224}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":224,\"outFeatures\":637}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":637,\"outFeatures\":170}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x27x27 image with 57 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-142\nComponents:\n - input (input) params={\"shape\":[1,3,27,27]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,27,27]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":17,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":17,\"outChannels\":58,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":58,\"outFeatures\":57}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 242-token sequences with 9 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-143\nComponents:\n - input (input) params={\"shape\":[1,242]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,242]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":12463,\"embeddingDim\":78}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":78,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":78,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":78,\"outFeatures\":9}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 456-token sequences with 68 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-144\nComponents:\n - input (input) params={\"shape\":[1,456]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,456]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":30428,\"embeddingDim\":336}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":336,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[336]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":336,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[336]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":336,\"outFeatures\":68}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 2493-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-146\nComponents:\n - input (input) params={\"shape\":[1,156]}\n - fc1 (linear) params={\"inFeatures\":156,\"outFeatures\":2493}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2493,\"outFeatures\":2493}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2493,\"outFeatures\":2493}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":2493,\"outFeatures\":11}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":156,\"outFeatures\":147}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":147,\"outFeatures\":147}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":147,\"outFeatures\":147}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":147,\"outFeatures\":11}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 252-feature, 50-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-147\nComponents:\n - input (input) params={\"shape\":[1,252]}\n - fc1 (linear) params={\"inFeatures\":252,\"outFeatures\":107}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":107,\"outFeatures\":119}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":119,\"outFeatures\":360}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":360,\"outFeatures\":363}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":363,\"outFeatures\":50}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":107}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":119}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":360}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":363}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 75-feature user input and a 117-feature item input, each through its own 2-layer MLP tower ending at width 260, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-148\nComponents:\n - user_input (input) params={\"shape\":[1,75]}\n - item_input (input) params={\"shape\":[1,117]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,75]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,117]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":75,\"outFeatures\":260}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":260,\"outFeatures\":260}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":117,\"outFeatures\":260}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":260,\"outFeatures\":260}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":520,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (104-feature input, 2 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-149\nComponents:\n - input (input) params={\"shape\":[1,104]}\n - fc1 (linear) params={\"inFeatures\":104,\"outFeatures\":4}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":4,\"outFeatures\":4}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":4,\"outFeatures\":2}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":104,\"outFeatures\":1377}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1377,\"outFeatures\":1377}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1377,\"outFeatures\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 131-feature input with 93 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-150\nComponents:\n - input (input) params={\"shape\":[1,131]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,131]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":131,\"outFeatures\":809}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":809,\"outFeatures\":658}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":658,\"outFeatures\":520}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":520,\"outFeatures\":413}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":413,\"outFeatures\":93}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1622-dim input: encode down to a 8-dim bottleneck and decode back to 1622. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-151\nComponents:\n - input (input) params={\"shape\":[1,1622]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1622]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1622,\"outFeatures\":1022}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":1022,\"outFeatures\":8}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":8,\"outFeatures\":1022}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":1022,\"outFeatures\":1622}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x61x61 image with 14 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-152\nComponents:\n - input (input) params={\"shape\":[1,3,61,61]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,61,61]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":63,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":63,\"outChannels\":31,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":31,\"outChannels\":39,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":39,\"outFeatures\":14}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 431-token sequences with 40 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-153\nComponents:\n - input (input) params={\"shape\":[1,431]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,431]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":42731,\"embeddingDim\":126}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":126,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":126,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":126,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":126,\"outFeatures\":40}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 141-token sequences with 81 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-154\nComponents:\n - input (input) params={\"shape\":[1,141]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,141]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":12162,\"embeddingDim\":64}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":64,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[64]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":64,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[64]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":64,\"outFeatures\":81}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (204) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-155\nComponents:\n - input (input) params={\"shape\":[1,49]}\n - embed (embedding) params={\"numEmbeddings\":13059,\"embeddingDim\":204}\n - attn (multiHeadAttention) params={\"embedDim\":204,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":204,\"outFeatures\":11}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":4}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 3442-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-156\nComponents:\n - input (input) params={\"shape\":[1,224]}\n - fc1 (linear) params={\"inFeatures\":224,\"outFeatures\":3442}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3442,\"outFeatures\":3442}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":3442,\"outFeatures\":31}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":224,\"outFeatures\":71}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":71,\"outFeatures\":71}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":71,\"outFeatures\":31}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 66-feature, 54-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-157\nComponents:\n - input (input) params={\"shape\":[1,66]}\n - fc1 (linear) params={\"inFeatures\":66,\"outFeatures\":93}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":93,\"outFeatures\":445}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":445,\"outFeatures\":195}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":195,\"outFeatures\":54}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":93}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":445}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":195}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 160-feature user input and a 127-feature item input, each through its own 2-layer MLP tower ending at width 343, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-158\nComponents:\n - user_input (input) params={\"shape\":[1,160]}\n - item_input (input) params={\"shape\":[1,127]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,160]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,127]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":160,\"outFeatures\":343}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":343,\"outFeatures\":343}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":127,\"outFeatures\":343}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":343,\"outFeatures\":343}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":686,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (112-feature input, 12 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-159\nComponents:\n - input (input) params={\"shape\":[1,112]}\n - fc1 (linear) params={\"inFeatures\":112,\"outFeatures\":6}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":6,\"outFeatures\":6}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":6,\"outFeatures\":12}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":112,\"outFeatures\":914}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":914,\"outFeatures\":914}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":914,\"outFeatures\":12}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 250-feature input with 51 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-160\nComponents:\n - input (input) params={\"shape\":[1,250]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,250]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":250,\"outFeatures\":647}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":647,\"outFeatures\":119}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":119,\"outFeatures\":537}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":537,\"outFeatures\":669}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":669,\"outFeatures\":507}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":507,\"outFeatures\":51}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1505-dim input: encode down to a 220-dim bottleneck and decode back to 1505. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-161\nComponents:\n - input (input) params={\"shape\":[1,1505]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1505]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1505,\"outFeatures\":272}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":272,\"outFeatures\":220}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":220,\"outFeatures\":272}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":272,\"outFeatures\":1505}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x56x56 image with 66 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-162\nComponents:\n - input (input) params={\"shape\":[1,3,56,56]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,56,56]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":15,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":15,\"outChannels\":43,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":43,\"outFeatures\":66}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 108-token sequences with 82 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-163\nComponents:\n - input (input) params={\"shape\":[1,108]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,108]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":22730,\"embeddingDim\":82}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":82,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":82,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":82,\"outFeatures\":82}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 502-token sequences with 76 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-164\nComponents:\n - input (input) params={\"shape\":[1,502]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,502]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":25252,\"embeddingDim\":688}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":688,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[688]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":688,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[688]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":688,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[688]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":688,\"outFeatures\":76}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (252) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-165\nComponents:\n - input (input) params={\"shape\":[1,480]}\n - embed (embedding) params={\"numEmbeddings\":31591,\"embeddingDim\":252}\n - attn (multiHeadAttention) params={\"embedDim\":252,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":252,\"outFeatures\":40}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":4}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 1642-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-166\nComponents:\n - input (input) params={\"shape\":[1,216]}\n - fc1 (linear) params={\"inFeatures\":216,\"outFeatures\":1642}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":1642,\"outFeatures\":1642}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":1642,\"outFeatures\":46}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":216,\"outFeatures\":200}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":200,\"outFeatures\":200}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":200,\"outFeatures\":46}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 147-feature, 21-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-167\nComponents:\n - input (input) params={\"shape\":[1,147]}\n - fc1 (linear) params={\"inFeatures\":147,\"outFeatures\":453}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":453,\"outFeatures\":348}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":348,\"outFeatures\":46}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":46,\"outFeatures\":237}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":237,\"outFeatures\":21}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":453}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":348}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":46}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":237}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 116-feature user input and a 35-feature item input, each through its own 2-layer MLP tower ending at width 339, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-168\nComponents:\n - user_input (input) params={\"shape\":[1,116]}\n - item_input (input) params={\"shape\":[1,35]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,116]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,35]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":116,\"outFeatures\":339}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":339,\"outFeatures\":339}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":35,\"outFeatures\":339}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":339,\"outFeatures\":339}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":678,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (119-feature input, 28 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-169\nComponents:\n - input (input) params={\"shape\":[1,119]}\n - fc1 (linear) params={\"inFeatures\":119,\"outFeatures\":6}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":6,\"outFeatures\":6}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":6,\"outFeatures\":28}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":119,\"outFeatures\":1059}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1059,\"outFeatures\":1059}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1059,\"outFeatures\":28}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 86-feature input with 189 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-170\nComponents:\n - input (input) params={\"shape\":[1,86]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,86]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":86,\"outFeatures\":217}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":217,\"outFeatures\":731}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":731,\"outFeatures\":189}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 199-dim input: encode down to a 191-dim bottleneck and decode back to 199. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-171\nComponents:\n - input (input) params={\"shape\":[1,199]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,199]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":199,\"outFeatures\":581}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":581,\"outFeatures\":191}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":191,\"outFeatures\":581}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":581,\"outFeatures\":199}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x64x64 image with 95 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-172\nComponents:\n - input (input) params={\"shape\":[1,3,64,64]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,64,64]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":30,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":30,\"outChannels\":61,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":61,\"outFeatures\":95}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 159-token sequences with 28 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-173\nComponents:\n - input (input) params={\"shape\":[1,159]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,159]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":33501,\"embeddingDim\":88}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":88,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":88,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":88,\"outFeatures\":28}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 434-token sequences with 28 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-174\nComponents:\n - input (input) params={\"shape\":[1,434]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,434]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":47369,\"embeddingDim\":208}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":208,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[208]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":208,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[208]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":208,\"outFeatures\":28}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 4082-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-176\nComponents:\n - input (input) params={\"shape\":[1,145]}\n - fc1 (linear) params={\"inFeatures\":145,\"outFeatures\":4082}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":4082,\"outFeatures\":4082}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":4082,\"outFeatures\":4082}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":4082,\"outFeatures\":8}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":145,\"outFeatures\":259}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":259,\"outFeatures\":259}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":259,\"outFeatures\":259}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":259,\"outFeatures\":8}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 216-feature, 54-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-177\nComponents:\n - input (input) params={\"shape\":[1,216]}\n - fc1 (linear) params={\"inFeatures\":216,\"outFeatures\":451}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":451,\"outFeatures\":159}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":159,\"outFeatures\":287}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":287,\"outFeatures\":272}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":272,\"outFeatures\":54}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":451}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":159}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":287}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":272}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 63-feature user input and a 82-feature item input, each through its own 2-layer MLP tower ending at width 269, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-178\nComponents:\n - user_input (input) params={\"shape\":[1,63]}\n - item_input (input) params={\"shape\":[1,82]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,63]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,82]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":63,\"outFeatures\":269}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":269,\"outFeatures\":269}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":82,\"outFeatures\":269}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":269,\"outFeatures\":269}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":538,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (46-feature input, 43 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-179\nComponents:\n - input (input) params={\"shape\":[1,46]}\n - fc1 (linear) params={\"inFeatures\":46,\"outFeatures\":24}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":24,\"outFeatures\":24}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":24,\"outFeatures\":43}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":46,\"outFeatures\":985}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":985,\"outFeatures\":985}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":985,\"outFeatures\":43}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 12-feature input with 56 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-180\nComponents:\n - input (input) params={\"shape\":[1,12]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,12]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":12,\"outFeatures\":73}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":73,\"outFeatures\":190}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":190,\"outFeatures\":16}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":16,\"outFeatures\":936}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":936,\"outFeatures\":56}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 754-dim input: encode down to a 81-dim bottleneck and decode back to 754. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-181\nComponents:\n - input (input) params={\"shape\":[1,754]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,754]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":754,\"outFeatures\":170}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":170,\"outFeatures\":81}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":81,\"outFeatures\":170}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":170,\"outFeatures\":754}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x56x56 image with 50 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-182\nComponents:\n - input (input) params={\"shape\":[1,3,56,56]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,56,56]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":31,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":31,\"outChannels\":46,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":46,\"outFeatures\":50}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 60-token sequences with 42 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-183\nComponents:\n - input (input) params={\"shape\":[1,60]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,60]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":39489,\"embeddingDim\":280}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":280,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":280,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":280,\"outFeatures\":42}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 157-token sequences with 48 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-184\nComponents:\n - input (input) params={\"shape\":[1,157]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,157]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":27555,\"embeddingDim\":344}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":344,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[344]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":344,\"outFeatures\":48}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (208) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-185\nComponents:\n - input (input) params={\"shape\":[1,464]}\n - embed (embedding) params={\"numEmbeddings\":47880,\"embeddingDim\":208}\n - attn (multiHeadAttention) params={\"embedDim\":208,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":208,\"outFeatures\":32}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":16}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 2016-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-186\nComponents:\n - input (input) params={\"shape\":[1,178]}\n - fc1 (linear) params={\"inFeatures\":178,\"outFeatures\":2016}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2016,\"outFeatures\":2016}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":2016,\"outFeatures\":20}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":178,\"outFeatures\":82}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":82,\"outFeatures\":82}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":82,\"outFeatures\":20}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 168-feature, 75-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-187\nComponents:\n - input (input) params={\"shape\":[1,168]}\n - fc1 (linear) params={\"inFeatures\":168,\"outFeatures\":225}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":225,\"outFeatures\":416}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":416,\"outFeatures\":158}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":158,\"outFeatures\":133}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":133,\"outFeatures\":293}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":293,\"outFeatures\":75}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":225}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":416}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":158}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":133}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":293}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 183-feature user input and a 222-feature item input, each through its own 2-layer MLP tower ending at width 438, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-188\nComponents:\n - user_input (input) params={\"shape\":[1,183]}\n - item_input (input) params={\"shape\":[1,222]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,183]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,222]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":183,\"outFeatures\":438}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":438,\"outFeatures\":438}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":222,\"outFeatures\":438}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":438,\"outFeatures\":438}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":876,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (51-feature input, 9 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-189\nComponents:\n - input (input) params={\"shape\":[1,51]}\n - fc1 (linear) params={\"inFeatures\":51,\"outFeatures\":13}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":13,\"outFeatures\":13}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":13,\"outFeatures\":9}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":51,\"outFeatures\":742}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":742,\"outFeatures\":742}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":742,\"outFeatures\":9}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 338-feature input with 148 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-190\nComponents:\n - input (input) params={\"shape\":[1,338]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,338]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":338,\"outFeatures\":702}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":702,\"outFeatures\":398}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":398,\"outFeatures\":847}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":847,\"outFeatures\":148}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 333-dim input: encode down to a 32-dim bottleneck and decode back to 333. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-191\nComponents:\n - input (input) params={\"shape\":[1,333]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,333]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":333,\"outFeatures\":475}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":475,\"outFeatures\":32}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":32,\"outFeatures\":475}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":475,\"outFeatures\":333}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x34x34 image with 39 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-192\nComponents:\n - input (input) params={\"shape\":[1,3,34,34]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,34,34]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":32,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":32,\"outChannels\":55,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":55,\"outChannels\":32,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":32,\"outFeatures\":39}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 251-token sequences with 100 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-193\nComponents:\n - input (input) params={\"shape\":[1,251]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,251]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":14481,\"embeddingDim\":106}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":106,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":106,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":106,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":106,\"outFeatures\":100}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 293-token sequences with 27 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-194\nComponents:\n - input (input) params={\"shape\":[1,293]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,293]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":29707,\"embeddingDim\":200}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":200,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[200]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":200,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[200]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":200,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[200]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":200,\"outFeatures\":27}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 3805-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-196\nComponents:\n - input (input) params={\"shape\":[1,228]}\n - fc1 (linear) params={\"inFeatures\":228,\"outFeatures\":3805}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3805,\"outFeatures\":3805}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":3805,\"outFeatures\":11}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":228,\"outFeatures\":335}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":335,\"outFeatures\":335}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":335,\"outFeatures\":11}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 100-feature, 32-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-197\nComponents:\n - input (input) params={\"shape\":[1,100]}\n - fc1 (linear) params={\"inFeatures\":100,\"outFeatures\":244}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":244,\"outFeatures\":379}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":379,\"outFeatures\":32}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":244}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":379}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 167-feature user input and a 160-feature item input, each through its own 2-layer MLP tower ending at width 106, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-198\nComponents:\n - user_input (input) params={\"shape\":[1,167]}\n - item_input (input) params={\"shape\":[1,160]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,167]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,160]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":167,\"outFeatures\":106}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":106,\"outFeatures\":106}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":160,\"outFeatures\":106}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":106,\"outFeatures\":106}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":212,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (115-feature input, 21 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-199\nComponents:\n - input (input) params={\"shape\":[1,115]}\n - fc1 (linear) params={\"inFeatures\":115,\"outFeatures\":10}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":10,\"outFeatures\":10}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":10,\"outFeatures\":21}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":115,\"outFeatures\":984}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":984,\"outFeatures\":984}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":984,\"outFeatures\":21}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 360-feature input with 196 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-200\nComponents:\n - input (input) params={\"shape\":[1,360]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,360]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":360,\"outFeatures\":99}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":99,\"outFeatures\":421}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":421,\"outFeatures\":958}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":958,\"outFeatures\":60}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":60,\"outFeatures\":137}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":137,\"outFeatures\":196}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 289-dim input: encode down to a 204-dim bottleneck and decode back to 289. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-201\nComponents:\n - input (input) params={\"shape\":[1,289]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,289]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":289,\"outFeatures\":600}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":600,\"outFeatures\":204}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":204,\"outFeatures\":600}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":600,\"outFeatures\":289}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x63x63 image with 5 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-202\nComponents:\n - input (input) params={\"shape\":[1,3,63,63]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,63,63]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":56,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":56,\"outChannels\":37,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":37,\"outChannels\":45,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":45,\"outFeatures\":5}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 393-token sequences with 17 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-203\nComponents:\n - input (input) params={\"shape\":[1,393]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,393]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":11477,\"embeddingDim\":44}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":44,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":44,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":44,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":44,\"outFeatures\":17}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 381-token sequences with 67 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-204\nComponents:\n - input (input) params={\"shape\":[1,381]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,381]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":14836,\"embeddingDim\":240}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":240,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[240]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":240,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[240]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":240,\"outFeatures\":67}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (312) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-205\nComponents:\n - input (input) params={\"shape\":[1,434]}\n - embed (embedding) params={\"numEmbeddings\":26148,\"embeddingDim\":312}\n - attn (multiHeadAttention) params={\"embedDim\":312,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":312,\"outFeatures\":4}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":8}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 3660-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-206\nComponents:\n - input (input) params={\"shape\":[1,116]}\n - fc1 (linear) params={\"inFeatures\":116,\"outFeatures\":3660}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3660,\"outFeatures\":3660}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3660,\"outFeatures\":3660}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":3660,\"outFeatures\":29}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":116,\"outFeatures\":197}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":197,\"outFeatures\":197}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":197,\"outFeatures\":197}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":197,\"outFeatures\":29}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 232-feature, 74-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-207\nComponents:\n - input (input) params={\"shape\":[1,232]}\n - fc1 (linear) params={\"inFeatures\":232,\"outFeatures\":472}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":472,\"outFeatures\":209}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":209,\"outFeatures\":74}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":472}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":209}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 21-feature user input and a 117-feature item input, each through its own 2-layer MLP tower ending at width 433, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-208\nComponents:\n - user_input (input) params={\"shape\":[1,21]}\n - item_input (input) params={\"shape\":[1,117]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,21]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,117]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":21,\"outFeatures\":433}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":433,\"outFeatures\":433}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":117,\"outFeatures\":433}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":433,\"outFeatures\":433}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":866,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (125-feature input, 26 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-209\nComponents:\n - input (input) params={\"shape\":[1,125]}\n - fc1 (linear) params={\"inFeatures\":125,\"outFeatures\":7}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":7,\"outFeatures\":7}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":7,\"outFeatures\":26}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":125,\"outFeatures\":935}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":935,\"outFeatures\":935}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":935,\"outFeatures\":26}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 138-feature input with 45 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-210\nComponents:\n - input (input) params={\"shape\":[1,138]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,138]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":138,\"outFeatures\":203}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":203,\"outFeatures\":297}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":297,\"outFeatures\":452}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":452,\"outFeatures\":887}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":887,\"outFeatures\":414}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":414,\"outFeatures\":45}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 122-dim input: encode down to a 71-dim bottleneck and decode back to 122. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-211\nComponents:\n - input (input) params={\"shape\":[1,122]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,122]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":122,\"outFeatures\":826}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":826,\"outFeatures\":71}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":71,\"outFeatures\":826}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":826,\"outFeatures\":122}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x61x61 image with 91 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-212\nComponents:\n - input (input) params={\"shape\":[1,3,61,61]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,61,61]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":57,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":57,\"outChannels\":55,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":55,\"outFeatures\":91}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 275-token sequences with 37 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-213\nComponents:\n - input (input) params={\"shape\":[1,275]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,275]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":42828,\"embeddingDim\":252}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":252,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":252,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":252,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":252,\"outFeatures\":37}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 115-token sequences with 97 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-214\nComponents:\n - input (input) params={\"shape\":[1,115]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,115]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":27394,\"embeddingDim\":180}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":180,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[180]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":180,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[180]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":180,\"outFeatures\":97}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 2927-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-216\nComponents:\n - input (input) params={\"shape\":[1,126]}\n - fc1 (linear) params={\"inFeatures\":126,\"outFeatures\":2927}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2927,\"outFeatures\":2927}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2927,\"outFeatures\":2927}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":2927,\"outFeatures\":2927}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":2927,\"outFeatures\":17}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":126,\"outFeatures\":298}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":298,\"outFeatures\":298}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":298,\"outFeatures\":298}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":298,\"outFeatures\":298}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":298,\"outFeatures\":17}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 224-feature, 89-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-217\nComponents:\n - input (input) params={\"shape\":[1,224]}\n - fc1 (linear) params={\"inFeatures\":224,\"outFeatures\":285}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":285,\"outFeatures\":331}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":331,\"outFeatures\":89}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":285}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":331}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 137-feature user input and a 232-feature item input, each through its own 2-layer MLP tower ending at width 103, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-218\nComponents:\n - user_input (input) params={\"shape\":[1,137]}\n - item_input (input) params={\"shape\":[1,232]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,137]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,232]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":137,\"outFeatures\":103}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":103,\"outFeatures\":103}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":232,\"outFeatures\":103}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":103,\"outFeatures\":103}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":206,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (75-feature input, 19 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-219\nComponents:\n - input (input) params={\"shape\":[1,75]}\n - fc1 (linear) params={\"inFeatures\":75,\"outFeatures\":20}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":20,\"outFeatures\":20}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":20,\"outFeatures\":19}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":75,\"outFeatures\":1314}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1314,\"outFeatures\":1314}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1314,\"outFeatures\":19}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 113-feature input with 72 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-220\nComponents:\n - input (input) params={\"shape\":[1,113]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,113]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":113,\"outFeatures\":549}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":549,\"outFeatures\":1023}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":1023,\"outFeatures\":476}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":476,\"outFeatures\":72}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 170-dim input: encode down to a 216-dim bottleneck and decode back to 170. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-221\nComponents:\n - input (input) params={\"shape\":[1,170]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,170]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":170,\"outFeatures\":889}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":889,\"outFeatures\":216}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":216,\"outFeatures\":889}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":889,\"outFeatures\":170}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x46x46 image with 93 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-222\nComponents:\n - input (input) params={\"shape\":[1,3,46,46]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,46,46]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":28,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":28,\"outChannels\":23,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":23,\"outChannels\":9,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":9,\"outChannels\":9,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":9,\"outFeatures\":93}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 459-token sequences with 48 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-223\nComponents:\n - input (input) params={\"shape\":[1,459]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,459]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":38132,\"embeddingDim\":32}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":32,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":32,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":32,\"outFeatures\":48}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 38-token sequences with 31 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-224\nComponents:\n - input (input) params={\"shape\":[1,38]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,38]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":24648,\"embeddingDim\":496}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":496,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[496]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":496,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[496]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":496,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[496]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":496,\"outFeatures\":31}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (512) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-225\nComponents:\n - input (input) params={\"shape\":[1,313]}\n - embed (embedding) params={\"numEmbeddings\":48083,\"embeddingDim\":512}\n - attn (multiHeadAttention) params={\"embedDim\":512,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":512,\"outFeatures\":18}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":16}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 2252-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-226\nComponents:\n - input (input) params={\"shape\":[1,42]}\n - fc1 (linear) params={\"inFeatures\":42,\"outFeatures\":2252}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2252,\"outFeatures\":2252}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":2252,\"outFeatures\":48}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":42,\"outFeatures\":321}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":321,\"outFeatures\":321}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":321,\"outFeatures\":48}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 23-feature, 21-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-227\nComponents:\n - input (input) params={\"shape\":[1,23]}\n - fc1 (linear) params={\"inFeatures\":23,\"outFeatures\":127}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":127,\"outFeatures\":409}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":409,\"outFeatures\":419}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":419,\"outFeatures\":170}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":170,\"outFeatures\":21}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":127}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":409}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":419}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":170}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 220-feature user input and a 249-feature item input, each through its own 2-layer MLP tower ending at width 51, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-228\nComponents:\n - user_input (input) params={\"shape\":[1,220]}\n - item_input (input) params={\"shape\":[1,249]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,220]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,249]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":220,\"outFeatures\":51}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":51,\"outFeatures\":51}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":249,\"outFeatures\":51}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":51,\"outFeatures\":51}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":102,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (76-feature input, 16 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-229\nComponents:\n - input (input) params={\"shape\":[1,76]}\n - fc1 (linear) params={\"inFeatures\":76,\"outFeatures\":20}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":20,\"outFeatures\":20}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":20,\"outFeatures\":16}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":76,\"outFeatures\":1205}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1205,\"outFeatures\":1205}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1205,\"outFeatures\":16}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 330-feature input with 57 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-230\nComponents:\n - input (input) params={\"shape\":[1,330]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,330]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":330,\"outFeatures\":27}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":27,\"outFeatures\":729}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":729,\"outFeatures\":57}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 775-dim input: encode down to a 193-dim bottleneck and decode back to 775. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-231\nComponents:\n - input (input) params={\"shape\":[1,775]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,775]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":775,\"outFeatures\":304}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":304,\"outFeatures\":193}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":193,\"outFeatures\":304}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":304,\"outFeatures\":775}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x61x61 image with 97 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-232\nComponents:\n - input (input) params={\"shape\":[1,3,61,61]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,61,61]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":21,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":21,\"outChannels\":38,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":38,\"outChannels\":36,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":36,\"outChannels\":8,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":8,\"outFeatures\":97}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 69-token sequences with 48 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-233\nComponents:\n - input (input) params={\"shape\":[1,69]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,69]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":11383,\"embeddingDim\":100}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":100,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":100,\"outFeatures\":48}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 296-token sequences with 31 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-234\nComponents:\n - input (input) params={\"shape\":[1,296]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,296]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":25146,\"embeddingDim\":152}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":152,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[152]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":152,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[152]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":152,\"outFeatures\":31}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 2625-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-236\nComponents:\n - input (input) params={\"shape\":[1,112]}\n - fc1 (linear) params={\"inFeatures\":112,\"outFeatures\":2625}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2625,\"outFeatures\":2625}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2625,\"outFeatures\":2625}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":2625,\"outFeatures\":50}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":112,\"outFeatures\":350}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":350,\"outFeatures\":350}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":350,\"outFeatures\":350}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":350,\"outFeatures\":50}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 178-feature, 31-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-237\nComponents:\n - input (input) params={\"shape\":[1,178]}\n - fc1 (linear) params={\"inFeatures\":178,\"outFeatures\":334}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":334,\"outFeatures\":396}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":396,\"outFeatures\":480}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":480,\"outFeatures\":152}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":152,\"outFeatures\":202}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":202,\"outFeatures\":31}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":334}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":396}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":480}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":152}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":202}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 102-feature user input and a 137-feature item input, each through its own 2-layer MLP tower ending at width 478, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-238\nComponents:\n - user_input (input) params={\"shape\":[1,102]}\n - item_input (input) params={\"shape\":[1,137]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,102]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,137]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":102,\"outFeatures\":478}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":478,\"outFeatures\":478}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":137,\"outFeatures\":478}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":478,\"outFeatures\":478}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":956,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (19-feature input, 20 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-239\nComponents:\n - input (input) params={\"shape\":[1,19]}\n - fc1 (linear) params={\"inFeatures\":19,\"outFeatures\":4}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":4,\"outFeatures\":4}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":4,\"outFeatures\":20}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":19,\"outFeatures\":1116}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1116,\"outFeatures\":1116}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1116,\"outFeatures\":20}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 323-feature input with 91 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-240\nComponents:\n - input (input) params={\"shape\":[1,323]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,323]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":323,\"outFeatures\":47}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":47,\"outFeatures\":108}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":108,\"outFeatures\":16}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":16,\"outFeatures\":376}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":376,\"outFeatures\":391}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":391,\"outFeatures\":21}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":21,\"outFeatures\":91}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1664-dim input: encode down to a 221-dim bottleneck and decode back to 1664. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-241\nComponents:\n - input (input) params={\"shape\":[1,1664]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1664]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1664,\"outFeatures\":687}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":687,\"outFeatures\":221}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":221,\"outFeatures\":687}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":687,\"outFeatures\":1664}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x60x60 image with 75 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-242\nComponents:\n - input (input) params={\"shape\":[1,3,60,60]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,60,60]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":59,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":59,\"outChannels\":10,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":10,\"outChannels\":54,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":54,\"outChannels\":39,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":39,\"outFeatures\":75}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 345-token sequences with 2 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-243\nComponents:\n - input (input) params={\"shape\":[1,345]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,345]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":16901,\"embeddingDim\":116}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":116,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":116,\"outFeatures\":2}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 169-token sequences with 29 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-244\nComponents:\n - input (input) params={\"shape\":[1,169]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,169]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":47886,\"embeddingDim\":116}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":116,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[116]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":116,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[116]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":116,\"outFeatures\":29}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 3889-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-246\nComponents:\n - input (input) params={\"shape\":[1,188]}\n - fc1 (linear) params={\"inFeatures\":188,\"outFeatures\":3889}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3889,\"outFeatures\":3889}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3889,\"outFeatures\":3889}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":3889,\"outFeatures\":6}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":188,\"outFeatures\":237}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":237,\"outFeatures\":237}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":237,\"outFeatures\":237}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":237,\"outFeatures\":6}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 156-feature, 92-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-247\nComponents:\n - input (input) params={\"shape\":[1,156]}\n - fc1 (linear) params={\"inFeatures\":156,\"outFeatures\":134}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":134,\"outFeatures\":248}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":248,\"outFeatures\":92}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":134}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":248}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 193-feature user input and a 145-feature item input, each through its own 2-layer MLP tower ending at width 240, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-248\nComponents:\n - user_input (input) params={\"shape\":[1,193]}\n - item_input (input) params={\"shape\":[1,145]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,193]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,145]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":193,\"outFeatures\":240}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":240,\"outFeatures\":240}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":145,\"outFeatures\":240}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":240,\"outFeatures\":240}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":480,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (23-feature input, 36 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-249\nComponents:\n - input (input) params={\"shape\":[1,23]}\n - fc1 (linear) params={\"inFeatures\":23,\"outFeatures\":7}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":7,\"outFeatures\":7}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":7,\"outFeatures\":36}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":23,\"outFeatures\":753}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":753,\"outFeatures\":753}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":753,\"outFeatures\":36}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 321-feature input with 17 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-250\nComponents:\n - input (input) params={\"shape\":[1,321]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,321]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":321,\"outFeatures\":286}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":286,\"outFeatures\":91}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":91,\"outFeatures\":117}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":117,\"outFeatures\":959}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":959,\"outFeatures\":17}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 935-dim input: encode down to a 177-dim bottleneck and decode back to 935. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-251\nComponents:\n - input (input) params={\"shape\":[1,935]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,935]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":935,\"outFeatures\":441}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":441,\"outFeatures\":177}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":177,\"outFeatures\":441}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":441,\"outFeatures\":935}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x41x41 image with 25 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-252\nComponents:\n - input (input) params={\"shape\":[1,3,41,41]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,41,41]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":59,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":59,\"outChannels\":9,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":9,\"outChannels\":17,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":17,\"outFeatures\":25}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 147-token sequences with 94 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-253\nComponents:\n - input (input) params={\"shape\":[1,147]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,147]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":34855,\"embeddingDim\":288}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":288,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":288,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":288,\"outFeatures\":94}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 399-token sequences with 22 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-254\nComponents:\n - input (input) params={\"shape\":[1,399]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,399]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":17264,\"embeddingDim\":124}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":124,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[124]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":124,\"outFeatures\":22}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 2176-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-256\nComponents:\n - input (input) params={\"shape\":[1,181]}\n - fc1 (linear) params={\"inFeatures\":181,\"outFeatures\":2176}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2176,\"outFeatures\":2176}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2176,\"outFeatures\":2176}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":2176,\"outFeatures\":2176}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":2176,\"outFeatures\":17}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":181,\"outFeatures\":215}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":215,\"outFeatures\":215}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":215,\"outFeatures\":215}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":215,\"outFeatures\":215}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":215,\"outFeatures\":17}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 82-feature, 70-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-257\nComponents:\n - input (input) params={\"shape\":[1,82]}\n - fc1 (linear) params={\"inFeatures\":82,\"outFeatures\":397}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":397,\"outFeatures\":277}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":277,\"outFeatures\":285}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":285,\"outFeatures\":307}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":307,\"outFeatures\":70}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":397}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":277}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":285}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":307}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 109-feature user input and a 104-feature item input, each through its own 2-layer MLP tower ending at width 171, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-258\nComponents:\n - user_input (input) params={\"shape\":[1,109]}\n - item_input (input) params={\"shape\":[1,104]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,109]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,104]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":109,\"outFeatures\":171}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":171,\"outFeatures\":171}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":104,\"outFeatures\":171}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":171,\"outFeatures\":171}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":342,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (75-feature input, 50 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-259\nComponents:\n - input (input) params={\"shape\":[1,75]}\n - fc1 (linear) params={\"inFeatures\":75,\"outFeatures\":16}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":16,\"outFeatures\":16}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":16,\"outFeatures\":50}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":75,\"outFeatures\":913}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":913,\"outFeatures\":913}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":913,\"outFeatures\":50}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 276-feature input with 40 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-260\nComponents:\n - input (input) params={\"shape\":[1,276]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,276]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":276,\"outFeatures\":432}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":432,\"outFeatures\":40}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":40,\"outFeatures\":749}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":749,\"outFeatures\":602}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":602,\"outFeatures\":229}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":229,\"outFeatures\":741}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":741,\"outFeatures\":40}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1051-dim input: encode down to a 97-dim bottleneck and decode back to 1051. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-261\nComponents:\n - input (input) params={\"shape\":[1,1051]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1051]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1051,\"outFeatures\":246}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":246,\"outFeatures\":97}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":97,\"outFeatures\":246}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":246,\"outFeatures\":1051}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x43x43 image with 19 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-262\nComponents:\n - input (input) params={\"shape\":[1,3,43,43]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,43,43]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":38,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":38,\"outChannels\":42,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":42,\"outChannels\":54,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":54,\"outChannels\":10,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":10,\"outFeatures\":19}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 156-token sequences with 44 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-263\nComponents:\n - input (input) params={\"shape\":[1,156]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,156]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":19170,\"embeddingDim\":124}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":124,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":124,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":124,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":124,\"outFeatures\":44}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 279-token sequences with 82 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-264\nComponents:\n - input (input) params={\"shape\":[1,279]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,279]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":33643,\"embeddingDim\":256}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":256,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[256]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":256,\"outFeatures\":82}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (462) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-265\nComponents:\n - input (input) params={\"shape\":[1,32]}\n - embed (embedding) params={\"numEmbeddings\":22504,\"embeddingDim\":462}\n - attn (multiHeadAttention) params={\"embedDim\":462,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":462,\"outFeatures\":7}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 2391-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-266\nComponents:\n - input (input) params={\"shape\":[1,235]}\n - fc1 (linear) params={\"inFeatures\":235,\"outFeatures\":2391}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2391,\"outFeatures\":2391}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2391,\"outFeatures\":2391}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":2391,\"outFeatures\":33}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":235,\"outFeatures\":325}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":325,\"outFeatures\":325}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":325,\"outFeatures\":325}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":325,\"outFeatures\":33}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 119-feature, 84-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-267\nComponents:\n - input (input) params={\"shape\":[1,119]}\n - fc1 (linear) params={\"inFeatures\":119,\"outFeatures\":65}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":65,\"outFeatures\":318}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":318,\"outFeatures\":57}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":57,\"outFeatures\":182}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":182,\"outFeatures\":143}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":143,\"outFeatures\":84}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":65}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":318}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":57}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":182}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":143}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 146-feature user input and a 199-feature item input, each through its own 2-layer MLP tower ending at width 428, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-268\nComponents:\n - user_input (input) params={\"shape\":[1,146]}\n - item_input (input) params={\"shape\":[1,199]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,146]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,199]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":146,\"outFeatures\":428}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":428,\"outFeatures\":428}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":199,\"outFeatures\":428}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":428,\"outFeatures\":428}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":856,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (16-feature input, 5 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-269\nComponents:\n - input (input) params={\"shape\":[1,16]}\n - fc1 (linear) params={\"inFeatures\":16,\"outFeatures\":15}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":15,\"outFeatures\":15}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":15,\"outFeatures\":5}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":16,\"outFeatures\":684}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":684,\"outFeatures\":684}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":684,\"outFeatures\":5}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 13-feature input with 99 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-270\nComponents:\n - input (input) params={\"shape\":[1,13]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,13]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":13,\"outFeatures\":470}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":470,\"outFeatures\":367}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":367,\"outFeatures\":296}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":296,\"outFeatures\":1017}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":1017,\"outFeatures\":803}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":803,\"outFeatures\":99}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1287-dim input: encode down to a 230-dim bottleneck and decode back to 1287. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-271\nComponents:\n - input (input) params={\"shape\":[1,1287]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1287]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1287,\"outFeatures\":492}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":492,\"outFeatures\":230}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":230,\"outFeatures\":492}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":492,\"outFeatures\":1287}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x37x37 image with 3 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-272\nComponents:\n - input (input) params={\"shape\":[1,3,37,37]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,37,37]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":13,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":13,\"outChannels\":10,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":10,\"outChannels\":56,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":56,\"outFeatures\":3}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 372-token sequences with 58 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-273\nComponents:\n - input (input) params={\"shape\":[1,372]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,372]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":17292,\"embeddingDim\":108}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":108,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":108,\"outFeatures\":58}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 389-token sequences with 22 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-274\nComponents:\n - input (input) params={\"shape\":[1,389]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,389]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":22193,\"embeddingDim\":176}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":176,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[176]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":176,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[176]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":176,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[176]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":176,\"outFeatures\":22}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (214) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-275\nComponents:\n - input (input) params={\"shape\":[1,141]}\n - embed (embedding) params={\"numEmbeddings\":12922,\"embeddingDim\":214}\n - attn (multiHeadAttention) params={\"embedDim\":214,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":214,\"outFeatures\":72}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3789-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-276\nComponents:\n - input (input) params={\"shape\":[1,100]}\n - fc1 (linear) params={\"inFeatures\":100,\"outFeatures\":3789}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3789,\"outFeatures\":3789}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3789,\"outFeatures\":3789}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3789,\"outFeatures\":3789}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3789,\"outFeatures\":35}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":100,\"outFeatures\":173}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":173,\"outFeatures\":173}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":173,\"outFeatures\":173}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":173,\"outFeatures\":173}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":173,\"outFeatures\":35}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 233-feature, 84-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-277\nComponents:\n - input (input) params={\"shape\":[1,233]}\n - fc1 (linear) params={\"inFeatures\":233,\"outFeatures\":56}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":56,\"outFeatures\":100}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":100,\"outFeatures\":84}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":56}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":100}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 46-feature user input and a 132-feature item input, each through its own 2-layer MLP tower ending at width 497, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-278\nComponents:\n - user_input (input) params={\"shape\":[1,46]}\n - item_input (input) params={\"shape\":[1,132]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,46]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,132]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":46,\"outFeatures\":497}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":497,\"outFeatures\":497}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":132,\"outFeatures\":497}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":497,\"outFeatures\":497}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":994,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (93-feature input, 32 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-279\nComponents:\n - input (input) params={\"shape\":[1,93]}\n - fc1 (linear) params={\"inFeatures\":93,\"outFeatures\":23}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":23,\"outFeatures\":23}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":23,\"outFeatures\":32}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":93,\"outFeatures\":1263}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1263,\"outFeatures\":1263}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1263,\"outFeatures\":32}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 137-feature input with 54 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-280\nComponents:\n - input (input) params={\"shape\":[1,137]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,137]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":137,\"outFeatures\":957}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":957,\"outFeatures\":20}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":20,\"outFeatures\":54}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 603-dim input: encode down to a 74-dim bottleneck and decode back to 603. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-281\nComponents:\n - input (input) params={\"shape\":[1,603]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,603]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":603,\"outFeatures\":240}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":240,\"outFeatures\":74}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":74,\"outFeatures\":240}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":240,\"outFeatures\":603}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x46x46 image with 90 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-282\nComponents:\n - input (input) params={\"shape\":[1,3,46,46]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,46,46]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":29,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":29,\"outChannels\":43,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":43,\"outFeatures\":90}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 463-token sequences with 98 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-283\nComponents:\n - input (input) params={\"shape\":[1,463]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,463]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":14945,\"embeddingDim\":108}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":108,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":108,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":108,\"outFeatures\":98}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 462-token sequences with 10 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-284\nComponents:\n - input (input) params={\"shape\":[1,462]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,462]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":39733,\"embeddingDim\":224}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":224,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[224]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":224,\"outFeatures\":10}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 2400-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-286\nComponents:\n - input (input) params={\"shape\":[1,42]}\n - fc1 (linear) params={\"inFeatures\":42,\"outFeatures\":2400}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2400,\"outFeatures\":2400}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2400,\"outFeatures\":2400}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":2400,\"outFeatures\":2400}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":2400,\"outFeatures\":23}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":42,\"outFeatures\":283}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":283,\"outFeatures\":283}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":283,\"outFeatures\":283}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":283,\"outFeatures\":283}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":283,\"outFeatures\":23}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 180-feature, 78-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-287\nComponents:\n - input (input) params={\"shape\":[1,180]}\n - fc1 (linear) params={\"inFeatures\":180,\"outFeatures\":251}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":251,\"outFeatures\":139}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":139,\"outFeatures\":78}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":251}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":139}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 18-feature user input and a 94-feature item input, each through its own 2-layer MLP tower ending at width 268, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-288\nComponents:\n - user_input (input) params={\"shape\":[1,18]}\n - item_input (input) params={\"shape\":[1,94]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,18]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,94]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":18,\"outFeatures\":268}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":268,\"outFeatures\":268}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":94,\"outFeatures\":268}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":268,\"outFeatures\":268}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":536,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (99-feature input, 46 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-289\nComponents:\n - input (input) params={\"shape\":[1,99]}\n - fc1 (linear) params={\"inFeatures\":99,\"outFeatures\":9}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":9,\"outFeatures\":9}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":9,\"outFeatures\":46}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":99,\"outFeatures\":1362}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1362,\"outFeatures\":1362}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1362,\"outFeatures\":46}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 172-feature input with 158 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-290\nComponents:\n - input (input) params={\"shape\":[1,172]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,172]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":172,\"outFeatures\":708}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":708,\"outFeatures\":841}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":841,\"outFeatures\":750}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":750,\"outFeatures\":340}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":340,\"outFeatures\":610}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":610,\"outFeatures\":177}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":177,\"outFeatures\":158}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1299-dim input: encode down to a 159-dim bottleneck and decode back to 1299. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-291\nComponents:\n - input (input) params={\"shape\":[1,1299]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1299]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1299,\"outFeatures\":80}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":80,\"outFeatures\":159}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":159,\"outFeatures\":80}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":80,\"outFeatures\":1299}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x40x40 image with 86 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-292\nComponents:\n - input (input) params={\"shape\":[1,3,40,40]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,40,40]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":11,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":11,\"outChannels\":19,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":19,\"outChannels\":16,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":16,\"outFeatures\":86}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 481-token sequences with 2 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-293\nComponents:\n - input (input) params={\"shape\":[1,481]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,481]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":31903,\"embeddingDim\":312}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":312,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":312,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":312,\"outFeatures\":2}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 287-token sequences with 17 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-294\nComponents:\n - input (input) params={\"shape\":[1,287]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,287]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":36559,\"embeddingDim\":640}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":640,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[640]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":640,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[640]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":640,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[640]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":640,\"outFeatures\":17}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (134) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-295\nComponents:\n - input (input) params={\"shape\":[1,408]}\n - embed (embedding) params={\"numEmbeddings\":34651,\"embeddingDim\":134}\n - attn (multiHeadAttention) params={\"embedDim\":134,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":134,\"outFeatures\":9}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 3442-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-296\nComponents:\n - input (input) params={\"shape\":[1,59]}\n - fc1 (linear) params={\"inFeatures\":59,\"outFeatures\":3442}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3442,\"outFeatures\":3442}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3442,\"outFeatures\":3442}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":3442,\"outFeatures\":43}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":59,\"outFeatures\":82}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":82,\"outFeatures\":82}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":82,\"outFeatures\":82}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":82,\"outFeatures\":43}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 30-feature, 86-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-297\nComponents:\n - input (input) params={\"shape\":[1,30]}\n - fc1 (linear) params={\"inFeatures\":30,\"outFeatures\":409}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":409,\"outFeatures\":103}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":103,\"outFeatures\":82}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":82,\"outFeatures\":86}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":409}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":103}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":82}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 83-feature user input and a 168-feature item input, each through its own 2-layer MLP tower ending at width 167, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-298\nComponents:\n - user_input (input) params={\"shape\":[1,83]}\n - item_input (input) params={\"shape\":[1,168]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,83]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,168]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":83,\"outFeatures\":167}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":167,\"outFeatures\":167}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":168,\"outFeatures\":167}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":167,\"outFeatures\":167}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":334,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (34-feature input, 15 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-299\nComponents:\n - input (input) params={\"shape\":[1,34]}\n - fc1 (linear) params={\"inFeatures\":34,\"outFeatures\":9}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":9,\"outFeatures\":9}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":9,\"outFeatures\":15}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":34,\"outFeatures\":874}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":874,\"outFeatures\":874}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":874,\"outFeatures\":15}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 49-feature input with 93 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-300\nComponents:\n - input (input) params={\"shape\":[1,49]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,49]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":49,\"outFeatures\":790}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":790,\"outFeatures\":814}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":814,\"outFeatures\":207}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":207,\"outFeatures\":422}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":422,\"outFeatures\":396}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":396,\"outFeatures\":376}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":376,\"outFeatures\":93}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 640-dim input: encode down to a 27-dim bottleneck and decode back to 640. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-301\nComponents:\n - input (input) params={\"shape\":[1,640]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,640]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":640,\"outFeatures\":122}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":122,\"outFeatures\":27}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":27,\"outFeatures\":122}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":122,\"outFeatures\":640}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x32x32 image with 33 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-302\nComponents:\n - input (input) params={\"shape\":[1,3,32,32]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,32,32]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":43,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":43,\"outChannels\":8,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":8,\"outFeatures\":33}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 475-token sequences with 29 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-303\nComponents:\n - input (input) params={\"shape\":[1,475]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,475]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":13075,\"embeddingDim\":464}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":464,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":464,\"outFeatures\":29}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 171-token sequences with 97 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-304\nComponents:\n - input (input) params={\"shape\":[1,171]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,171]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":28445,\"embeddingDim\":180}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":180,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[180]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":180,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[180]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":180,\"outFeatures\":97}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (320) is not divisible by numHeads (7). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-305\nComponents:\n - input (input) params={\"shape\":[1,102]}\n - embed (embedding) params={\"numEmbeddings\":47465,\"embeddingDim\":320}\n - attn (multiHeadAttention) params={\"embedDim\":320,\"numHeads\":7}\n - head (linear) params={\"inFeatures\":320,\"outFeatures\":65}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":16}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 4070-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-306\nComponents:\n - input (input) params={\"shape\":[1,227]}\n - fc1 (linear) params={\"inFeatures\":227,\"outFeatures\":4070}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":4070,\"outFeatures\":4070}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":4070,\"outFeatures\":4070}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":4070,\"outFeatures\":28}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":227,\"outFeatures\":373}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":373,\"outFeatures\":373}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":373,\"outFeatures\":373}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":373,\"outFeatures\":28}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 61-feature, 99-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-307\nComponents:\n - input (input) params={\"shape\":[1,61]}\n - fc1 (linear) params={\"inFeatures\":61,\"outFeatures\":230}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":230,\"outFeatures\":141}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":141,\"outFeatures\":99}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":230}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":141}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 99-feature user input and a 69-feature item input, each through its own 2-layer MLP tower ending at width 210, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-308\nComponents:\n - user_input (input) params={\"shape\":[1,99]}\n - item_input (input) params={\"shape\":[1,69]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,99]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,69]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":99,\"outFeatures\":210}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":210,\"outFeatures\":210}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":69,\"outFeatures\":210}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":210,\"outFeatures\":210}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":420,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (110-feature input, 9 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-309\nComponents:\n - input (input) params={\"shape\":[1,110]}\n - fc1 (linear) params={\"inFeatures\":110,\"outFeatures\":13}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":13,\"outFeatures\":13}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":13,\"outFeatures\":9}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":110,\"outFeatures\":853}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":853,\"outFeatures\":853}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":853,\"outFeatures\":9}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 129-feature input with 6 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-310\nComponents:\n - input (input) params={\"shape\":[1,129]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,129]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":129,\"outFeatures\":104}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":104,\"outFeatures\":989}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":989,\"outFeatures\":631}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":631,\"outFeatures\":411}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":411,\"outFeatures\":132}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":132,\"outFeatures\":812}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":812,\"outFeatures\":6}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1673-dim input: encode down to a 80-dim bottleneck and decode back to 1673. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-311\nComponents:\n - input (input) params={\"shape\":[1,1673]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1673]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1673,\"outFeatures\":578}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":578,\"outFeatures\":80}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":80,\"outFeatures\":578}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":578,\"outFeatures\":1673}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x61x61 image with 49 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-312\nComponents:\n - input (input) params={\"shape\":[1,3,61,61]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,61,61]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":17,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":17,\"outChannels\":40,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":40,\"outChannels\":33,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":33,\"outChannels\":49,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":49,\"outFeatures\":49}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 310-token sequences with 76 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-313\nComponents:\n - input (input) params={\"shape\":[1,310]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,310]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":42762,\"embeddingDim\":172}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":172,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":172,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":172,\"outFeatures\":76}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 111-token sequences with 64 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-314\nComponents:\n - input (input) params={\"shape\":[1,111]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,111]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":13266,\"embeddingDim\":132}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":132,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[132]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":132,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[132]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":132,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[132]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":132,\"outFeatures\":64}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 3735-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-316\nComponents:\n - input (input) params={\"shape\":[1,221]}\n - fc1 (linear) params={\"inFeatures\":221,\"outFeatures\":3735}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3735,\"outFeatures\":3735}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":3735,\"outFeatures\":36}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":221,\"outFeatures\":347}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":347,\"outFeatures\":347}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":347,\"outFeatures\":36}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 19-feature, 75-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-317\nComponents:\n - input (input) params={\"shape\":[1,19]}\n - fc1 (linear) params={\"inFeatures\":19,\"outFeatures\":249}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":249,\"outFeatures\":98}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":98,\"outFeatures\":113}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":113,\"outFeatures\":296}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":296,\"outFeatures\":95}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":95,\"outFeatures\":75}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":249}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":98}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":113}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":296}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":95}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 214-feature user input and a 207-feature item input, each through its own 2-layer MLP tower ending at width 339, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-318\nComponents:\n - user_input (input) params={\"shape\":[1,214]}\n - item_input (input) params={\"shape\":[1,207]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,214]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,207]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":214,\"outFeatures\":339}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":339,\"outFeatures\":339}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":207,\"outFeatures\":339}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":339,\"outFeatures\":339}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":678,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (30-feature input, 29 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-319\nComponents:\n - input (input) params={\"shape\":[1,30]}\n - fc1 (linear) params={\"inFeatures\":30,\"outFeatures\":9}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":9,\"outFeatures\":9}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":9,\"outFeatures\":29}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":30,\"outFeatures\":1113}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1113,\"outFeatures\":1113}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1113,\"outFeatures\":29}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 114-feature input with 156 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-320\nComponents:\n - input (input) params={\"shape\":[1,114]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,114]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":114,\"outFeatures\":308}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":308,\"outFeatures\":158}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":158,\"outFeatures\":912}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":912,\"outFeatures\":685}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":685,\"outFeatures\":156}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1250-dim input: encode down to a 91-dim bottleneck and decode back to 1250. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-321\nComponents:\n - input (input) params={\"shape\":[1,1250]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1250]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1250,\"outFeatures\":219}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":219,\"outFeatures\":91}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":91,\"outFeatures\":219}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":219,\"outFeatures\":1250}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x28x28 image with 19 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-322\nComponents:\n - input (input) params={\"shape\":[1,3,28,28]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,28,28]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":31,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":31,\"outChannels\":48,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":48,\"outFeatures\":19}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 349-token sequences with 21 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-323\nComponents:\n - input (input) params={\"shape\":[1,349]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,349]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":11742,\"embeddingDim\":440}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":440,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":440,\"outFeatures\":21}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 202-token sequences with 22 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-324\nComponents:\n - input (input) params={\"shape\":[1,202]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,202]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":45612,\"embeddingDim\":40}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":40,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[40]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":40,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[40]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":40,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[40]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":40,\"outFeatures\":22}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3619-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-326\nComponents:\n - input (input) params={\"shape\":[1,69]}\n - fc1 (linear) params={\"inFeatures\":69,\"outFeatures\":3619}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3619,\"outFeatures\":3619}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3619,\"outFeatures\":3619}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3619,\"outFeatures\":3619}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3619,\"outFeatures\":43}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":69,\"outFeatures\":229}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":229,\"outFeatures\":229}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":229,\"outFeatures\":229}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":229,\"outFeatures\":229}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":229,\"outFeatures\":43}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 110-feature, 57-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-327\nComponents:\n - input (input) params={\"shape\":[1,110]}\n - fc1 (linear) params={\"inFeatures\":110,\"outFeatures\":169}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":169,\"outFeatures\":451}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":451,\"outFeatures\":407}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":407,\"outFeatures\":231}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":231,\"outFeatures\":484}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":484,\"outFeatures\":57}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":169}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":451}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":407}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":231}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":484}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 99-feature user input and a 183-feature item input, each through its own 2-layer MLP tower ending at width 263, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-328\nComponents:\n - user_input (input) params={\"shape\":[1,99]}\n - item_input (input) params={\"shape\":[1,183]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,99]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,183]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":99,\"outFeatures\":263}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":263,\"outFeatures\":263}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":183,\"outFeatures\":263}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":263,\"outFeatures\":263}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":526,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (27-feature input, 34 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-329\nComponents:\n - input (input) params={\"shape\":[1,27]}\n - fc1 (linear) params={\"inFeatures\":27,\"outFeatures\":14}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":14,\"outFeatures\":14}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":14,\"outFeatures\":34}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":27,\"outFeatures\":1287}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1287,\"outFeatures\":1287}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1287,\"outFeatures\":34}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 256-feature input with 177 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-330\nComponents:\n - input (input) params={\"shape\":[1,256]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,256]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":256,\"outFeatures\":330}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":330,\"outFeatures\":929}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":929,\"outFeatures\":993}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":993,\"outFeatures\":181}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":181,\"outFeatures\":106}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":106,\"outFeatures\":224}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":224,\"outFeatures\":177}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 900-dim input: encode down to a 217-dim bottleneck and decode back to 900. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-331\nComponents:\n - input (input) params={\"shape\":[1,900]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,900]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":900,\"outFeatures\":761}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":761,\"outFeatures\":217}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":217,\"outFeatures\":761}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":761,\"outFeatures\":900}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x27x27 image with 26 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-332\nComponents:\n - input (input) params={\"shape\":[1,3,27,27]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,27,27]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":59,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":59,\"outChannels\":12,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":12,\"outChannels\":61,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":61,\"outFeatures\":26}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 357-token sequences with 86 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-333\nComponents:\n - input (input) params={\"shape\":[1,357]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,357]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":22327,\"embeddingDim\":94}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":94,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":94,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":94,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":94,\"outFeatures\":86}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 46-token sequences with 91 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-334\nComponents:\n - input (input) params={\"shape\":[1,46]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,46]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":46865,\"embeddingDim\":92}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":92,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[92]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":92,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[92]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":92,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[92]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":92,\"outFeatures\":91}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (136) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-335\nComponents:\n - input (input) params={\"shape\":[1,246]}\n - embed (embedding) params={\"numEmbeddings\":32671,\"embeddingDim\":136}\n - attn (multiHeadAttention) params={\"embedDim\":136,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":136,\"outFeatures\":7}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":8}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 1536-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-336\nComponents:\n - input (input) params={\"shape\":[1,49]}\n - fc1 (linear) params={\"inFeatures\":49,\"outFeatures\":1536}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":1536,\"outFeatures\":1536}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":1536,\"outFeatures\":1536}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":1536,\"outFeatures\":37}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":49,\"outFeatures\":219}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":219,\"outFeatures\":219}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":219,\"outFeatures\":219}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":219,\"outFeatures\":37}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 99-feature, 13-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-337\nComponents:\n - input (input) params={\"shape\":[1,99]}\n - fc1 (linear) params={\"inFeatures\":99,\"outFeatures\":454}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":454,\"outFeatures\":79}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":79,\"outFeatures\":13}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":454}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":79}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 151-feature user input and a 29-feature item input, each through its own 2-layer MLP tower ending at width 427, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-338\nComponents:\n - user_input (input) params={\"shape\":[1,151]}\n - item_input (input) params={\"shape\":[1,29]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,151]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,29]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":151,\"outFeatures\":427}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":427,\"outFeatures\":427}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":29,\"outFeatures\":427}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":427,\"outFeatures\":427}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":854,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (96-feature input, 19 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-339\nComponents:\n - input (input) params={\"shape\":[1,96]}\n - fc1 (linear) params={\"inFeatures\":96,\"outFeatures\":15}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":15,\"outFeatures\":15}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":15,\"outFeatures\":19}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":96,\"outFeatures\":1386}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1386,\"outFeatures\":1386}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1386,\"outFeatures\":19}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 354-feature input with 168 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-340\nComponents:\n - input (input) params={\"shape\":[1,354]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,354]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":354,\"outFeatures\":145}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":145,\"outFeatures\":593}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":593,\"outFeatures\":90}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":90,\"outFeatures\":599}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":599,\"outFeatures\":185}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":185,\"outFeatures\":308}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":308,\"outFeatures\":168}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 813-dim input: encode down to a 200-dim bottleneck and decode back to 813. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-341\nComponents:\n - input (input) params={\"shape\":[1,813]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,813]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":813,\"outFeatures\":339}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":339,\"outFeatures\":200}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":200,\"outFeatures\":339}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":339,\"outFeatures\":813}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x50x50 image with 93 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-342\nComponents:\n - input (input) params={\"shape\":[1,3,50,50]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,50,50]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":22,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":22,\"outChannels\":61,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":61,\"outChannels\":49,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":49,\"outChannels\":23,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":23,\"outFeatures\":93}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 177-token sequences with 32 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-343\nComponents:\n - input (input) params={\"shape\":[1,177]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,177]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":41018,\"embeddingDim\":120}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":120,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":120,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":120,\"outFeatures\":32}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 380-token sequences with 53 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-344\nComponents:\n - input (input) params={\"shape\":[1,380]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,380]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":45240,\"embeddingDim\":384}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":384,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[384]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":384,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[384]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":384,\"outFeatures\":53}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 1687-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-346\nComponents:\n - input (input) params={\"shape\":[1,115]}\n - fc1 (linear) params={\"inFeatures\":115,\"outFeatures\":1687}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":1687,\"outFeatures\":1687}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":1687,\"outFeatures\":1687}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":1687,\"outFeatures\":1687}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":1687,\"outFeatures\":16}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":115,\"outFeatures\":366}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":366,\"outFeatures\":366}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":366,\"outFeatures\":366}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":366,\"outFeatures\":366}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":366,\"outFeatures\":16}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 197-feature, 60-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-347\nComponents:\n - input (input) params={\"shape\":[1,197]}\n - fc1 (linear) params={\"inFeatures\":197,\"outFeatures\":116}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":116,\"outFeatures\":220}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":220,\"outFeatures\":489}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":489,\"outFeatures\":100}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":100,\"outFeatures\":60}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":116}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":220}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":489}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":100}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 43-feature user input and a 98-feature item input, each through its own 2-layer MLP tower ending at width 127, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-348\nComponents:\n - user_input (input) params={\"shape\":[1,43]}\n - item_input (input) params={\"shape\":[1,98]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,43]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,98]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":43,\"outFeatures\":127}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":127,\"outFeatures\":127}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":98,\"outFeatures\":127}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":127,\"outFeatures\":127}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":254,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (23-feature input, 4 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-349\nComponents:\n - input (input) params={\"shape\":[1,23]}\n - fc1 (linear) params={\"inFeatures\":23,\"outFeatures\":19}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":19,\"outFeatures\":19}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":19,\"outFeatures\":4}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":23,\"outFeatures\":926}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":926,\"outFeatures\":926}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":926,\"outFeatures\":4}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 28-feature input with 156 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-350\nComponents:\n - input (input) params={\"shape\":[1,28]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,28]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":28,\"outFeatures\":478}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":478,\"outFeatures\":418}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":418,\"outFeatures\":952}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":952,\"outFeatures\":462}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":462,\"outFeatures\":156}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 213-dim input: encode down to a 194-dim bottleneck and decode back to 213. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-351\nComponents:\n - input (input) params={\"shape\":[1,213]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,213]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":213,\"outFeatures\":513}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":513,\"outFeatures\":194}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":194,\"outFeatures\":513}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":513,\"outFeatures\":213}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x47x47 image with 79 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-352\nComponents:\n - input (input) params={\"shape\":[1,3,47,47]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,47,47]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":23,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":23,\"outChannels\":34,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":34,\"outChannels\":37,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":37,\"outFeatures\":79}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 232-token sequences with 77 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-353\nComponents:\n - input (input) params={\"shape\":[1,232]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,232]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":39133,\"embeddingDim\":44}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":44,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":44,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":44,\"outFeatures\":77}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 283-token sequences with 96 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-354\nComponents:\n - input (input) params={\"shape\":[1,283]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,283]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":25062,\"embeddingDim\":272}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":272,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[272]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":272,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[272]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":272,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[272]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":272,\"outFeatures\":96}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (404) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-355\nComponents:\n - input (input) params={\"shape\":[1,162]}\n - embed (embedding) params={\"numEmbeddings\":40346,\"embeddingDim\":404}\n - attn (multiHeadAttention) params={\"embedDim\":404,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":404,\"outFeatures\":75}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":4}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 2192-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-356\nComponents:\n - input (input) params={\"shape\":[1,87]}\n - fc1 (linear) params={\"inFeatures\":87,\"outFeatures\":2192}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2192,\"outFeatures\":2192}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2192,\"outFeatures\":2192}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":2192,\"outFeatures\":2192}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":2192,\"outFeatures\":17}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":87,\"outFeatures\":64}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":64,\"outFeatures\":64}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":64,\"outFeatures\":64}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":64,\"outFeatures\":64}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":64,\"outFeatures\":17}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 219-feature, 42-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-357\nComponents:\n - input (input) params={\"shape\":[1,219]}\n - fc1 (linear) params={\"inFeatures\":219,\"outFeatures\":364}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":364,\"outFeatures\":229}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":229,\"outFeatures\":71}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":71,\"outFeatures\":42}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":364}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":229}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":71}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 242-feature user input and a 23-feature item input, each through its own 2-layer MLP tower ending at width 291, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-358\nComponents:\n - user_input (input) params={\"shape\":[1,242]}\n - item_input (input) params={\"shape\":[1,23]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,242]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,23]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":242,\"outFeatures\":291}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":291,\"outFeatures\":291}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":23,\"outFeatures\":291}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":291,\"outFeatures\":291}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":582,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (60-feature input, 24 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-359\nComponents:\n - input (input) params={\"shape\":[1,60]}\n - fc1 (linear) params={\"inFeatures\":60,\"outFeatures\":11}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":11,\"outFeatures\":11}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":11,\"outFeatures\":24}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":60,\"outFeatures\":1123}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1123,\"outFeatures\":1123}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1123,\"outFeatures\":24}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 279-feature input with 23 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-360\nComponents:\n - input (input) params={\"shape\":[1,279]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,279]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":279,\"outFeatures\":118}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":118,\"outFeatures\":609}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":609,\"outFeatures\":866}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":866,\"outFeatures\":557}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":557,\"outFeatures\":23}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1064-dim input: encode down to a 119-dim bottleneck and decode back to 1064. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-361\nComponents:\n - input (input) params={\"shape\":[1,1064]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1064]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1064,\"outFeatures\":861}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":861,\"outFeatures\":119}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":119,\"outFeatures\":861}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":861,\"outFeatures\":1064}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x37x37 image with 57 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-362\nComponents:\n - input (input) params={\"shape\":[1,3,37,37]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,37,37]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":9,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":9,\"outChannels\":15,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":15,\"outChannels\":50,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":50,\"outChannels\":42,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":42,\"outFeatures\":57}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 210-token sequences with 41 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-363\nComponents:\n - input (input) params={\"shape\":[1,210]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,210]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":9953,\"embeddingDim\":80}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":80,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":80,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":80,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":80,\"outFeatures\":41}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 304-token sequences with 21 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-364\nComponents:\n - input (input) params={\"shape\":[1,304]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,304]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":21145,\"embeddingDim\":704}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":704,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[704]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":704,\"outFeatures\":21}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 2267-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-366\nComponents:\n - input (input) params={\"shape\":[1,182]}\n - fc1 (linear) params={\"inFeatures\":182,\"outFeatures\":2267}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2267,\"outFeatures\":2267}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":2267,\"outFeatures\":46}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":182,\"outFeatures\":255}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":255,\"outFeatures\":255}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":255,\"outFeatures\":46}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 67-feature, 14-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-367\nComponents:\n - input (input) params={\"shape\":[1,67]}\n - fc1 (linear) params={\"inFeatures\":67,\"outFeatures\":371}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":371,\"outFeatures\":424}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":424,\"outFeatures\":14}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":371}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":424}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 250-feature user input and a 47-feature item input, each through its own 2-layer MLP tower ending at width 200, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-368\nComponents:\n - user_input (input) params={\"shape\":[1,250]}\n - item_input (input) params={\"shape\":[1,47]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,250]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,47]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":250,\"outFeatures\":200}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":200,\"outFeatures\":200}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":47,\"outFeatures\":200}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":200,\"outFeatures\":200}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":400,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (113-feature input, 49 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-369\nComponents:\n - input (input) params={\"shape\":[1,113]}\n - fc1 (linear) params={\"inFeatures\":113,\"outFeatures\":14}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":14,\"outFeatures\":14}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":14,\"outFeatures\":49}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":113,\"outFeatures\":921}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":921,\"outFeatures\":921}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":921,\"outFeatures\":49}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 243-feature input with 152 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-370\nComponents:\n - input (input) params={\"shape\":[1,243]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,243]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":243,\"outFeatures\":225}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":225,\"outFeatures\":149}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":149,\"outFeatures\":534}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":534,\"outFeatures\":458}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":458,\"outFeatures\":152}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 939-dim input: encode down to a 214-dim bottleneck and decode back to 939. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-371\nComponents:\n - input (input) params={\"shape\":[1,939]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,939]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":939,\"outFeatures\":80}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":80,\"outFeatures\":214}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":214,\"outFeatures\":80}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":80,\"outFeatures\":939}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x63x63 image with 23 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-372\nComponents:\n - input (input) params={\"shape\":[1,3,63,63]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,63,63]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":39,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":39,\"outChannels\":19,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":19,\"outChannels\":15,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":15,\"outChannels\":23,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":23,\"outFeatures\":23}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 384-token sequences with 8 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-373\nComponents:\n - input (input) params={\"shape\":[1,384]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,384]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":26804,\"embeddingDim\":200}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":200,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":200,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":200,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":200,\"outFeatures\":8}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 297-token sequences with 19 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-374\nComponents:\n - input (input) params={\"shape\":[1,297]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,297]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":8407,\"embeddingDim\":432}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":432,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[432]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":432,\"outFeatures\":19}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 3783-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-376\nComponents:\n - input (input) params={\"shape\":[1,172]}\n - fc1 (linear) params={\"inFeatures\":172,\"outFeatures\":3783}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3783,\"outFeatures\":3783}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":3783,\"outFeatures\":6}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":172,\"outFeatures\":120}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":120,\"outFeatures\":120}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":120,\"outFeatures\":6}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 150-feature, 2-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-377\nComponents:\n - input (input) params={\"shape\":[1,150]}\n - fc1 (linear) params={\"inFeatures\":150,\"outFeatures\":152}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":152,\"outFeatures\":374}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":374,\"outFeatures\":275}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":275,\"outFeatures\":145}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":145,\"outFeatures\":82}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":82,\"outFeatures\":2}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":152}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":374}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":275}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":145}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":82}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 20-feature user input and a 16-feature item input, each through its own 2-layer MLP tower ending at width 502, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-378\nComponents:\n - user_input (input) params={\"shape\":[1,20]}\n - item_input (input) params={\"shape\":[1,16]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,20]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,16]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":20,\"outFeatures\":502}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":502,\"outFeatures\":502}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":16,\"outFeatures\":502}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":502,\"outFeatures\":502}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":1004,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (68-feature input, 4 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-379\nComponents:\n - input (input) params={\"shape\":[1,68]}\n - fc1 (linear) params={\"inFeatures\":68,\"outFeatures\":22}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":22,\"outFeatures\":22}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":22,\"outFeatures\":4}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":68,\"outFeatures\":1070}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1070,\"outFeatures\":1070}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1070,\"outFeatures\":4}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 325-feature input with 101 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-380\nComponents:\n - input (input) params={\"shape\":[1,325]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,325]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":325,\"outFeatures\":700}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":700,\"outFeatures\":646}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":646,\"outFeatures\":274}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":274,\"outFeatures\":923}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":923,\"outFeatures\":101}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1425-dim input: encode down to a 211-dim bottleneck and decode back to 1425. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-381\nComponents:\n - input (input) params={\"shape\":[1,1425]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1425]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1425,\"outFeatures\":303}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":303,\"outFeatures\":211}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":211,\"outFeatures\":303}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":303,\"outFeatures\":1425}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x36x36 image with 50 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-382\nComponents:\n - input (input) params={\"shape\":[1,3,36,36]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,36,36]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":14,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":14,\"outChannels\":26,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":26,\"outChannels\":12,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":12,\"outFeatures\":50}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 499-token sequences with 49 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-383\nComponents:\n - input (input) params={\"shape\":[1,499]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,499]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":27737,\"embeddingDim\":26}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":26,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":26,\"outFeatures\":49}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 273-token sequences with 75 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-384\nComponents:\n - input (input) params={\"shape\":[1,273]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,273]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":46383,\"embeddingDim\":288}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":288,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[288]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":288,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[288]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":288,\"outFeatures\":75}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3820-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-386\nComponents:\n - input (input) params={\"shape\":[1,235]}\n - fc1 (linear) params={\"inFeatures\":235,\"outFeatures\":3820}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3820,\"outFeatures\":3820}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3820,\"outFeatures\":3820}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3820,\"outFeatures\":3820}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3820,\"outFeatures\":25}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":235,\"outFeatures\":301}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":301,\"outFeatures\":301}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":301,\"outFeatures\":301}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":301,\"outFeatures\":301}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":301,\"outFeatures\":25}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 212-feature, 42-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-387\nComponents:\n - input (input) params={\"shape\":[1,212]}\n - fc1 (linear) params={\"inFeatures\":212,\"outFeatures\":335}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":335,\"outFeatures\":40}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":40,\"outFeatures\":42}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":335}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":40}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 143-feature user input and a 53-feature item input, each through its own 2-layer MLP tower ending at width 168, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-388\nComponents:\n - user_input (input) params={\"shape\":[1,143]}\n - item_input (input) params={\"shape\":[1,53]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,143]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,53]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":143,\"outFeatures\":168}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":168,\"outFeatures\":168}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":53,\"outFeatures\":168}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":168,\"outFeatures\":168}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":336,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (61-feature input, 21 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-389\nComponents:\n - input (input) params={\"shape\":[1,61]}\n - fc1 (linear) params={\"inFeatures\":61,\"outFeatures\":23}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":23,\"outFeatures\":23}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":23,\"outFeatures\":21}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":61,\"outFeatures\":834}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":834,\"outFeatures\":834}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":834,\"outFeatures\":21}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 183-feature input with 181 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-390\nComponents:\n - input (input) params={\"shape\":[1,183]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,183]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":183,\"outFeatures\":347}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":347,\"outFeatures\":907}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":907,\"outFeatures\":524}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":524,\"outFeatures\":942}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":942,\"outFeatures\":181}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1151-dim input: encode down to a 237-dim bottleneck and decode back to 1151. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-391\nComponents:\n - input (input) params={\"shape\":[1,1151]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1151]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1151,\"outFeatures\":326}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":326,\"outFeatures\":237}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":237,\"outFeatures\":326}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":326,\"outFeatures\":1151}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x44x44 image with 37 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-392\nComponents:\n - input (input) params={\"shape\":[1,3,44,44]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,44,44]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":58,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":58,\"outChannels\":52,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":52,\"outChannels\":17,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":17,\"outFeatures\":37}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 408-token sequences with 14 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-393\nComponents:\n - input (input) params={\"shape\":[1,408]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,408]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":36274,\"embeddingDim\":106}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":106,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":106,\"outFeatures\":14}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 342-token sequences with 99 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-394\nComponents:\n - input (input) params={\"shape\":[1,342]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,342]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":33369,\"embeddingDim\":224}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":224,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[224]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":224,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[224]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":224,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[224]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":224,\"outFeatures\":99}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (484) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-395\nComponents:\n - input (input) params={\"shape\":[1,87]}\n - embed (embedding) params={\"numEmbeddings\":45955,\"embeddingDim\":484}\n - attn (multiHeadAttention) params={\"embedDim\":484,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":484,\"outFeatures\":83}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":4}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 2857-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-396\nComponents:\n - input (input) params={\"shape\":[1,222]}\n - fc1 (linear) params={\"inFeatures\":222,\"outFeatures\":2857}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2857,\"outFeatures\":2857}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2857,\"outFeatures\":2857}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":2857,\"outFeatures\":2857}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":2857,\"outFeatures\":28}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":222,\"outFeatures\":297}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":297,\"outFeatures\":297}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":297,\"outFeatures\":297}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":297,\"outFeatures\":297}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":297,\"outFeatures\":28}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 199-feature, 75-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-397\nComponents:\n - input (input) params={\"shape\":[1,199]}\n - fc1 (linear) params={\"inFeatures\":199,\"outFeatures\":378}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":378,\"outFeatures\":116}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":116,\"outFeatures\":346}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":346,\"outFeatures\":74}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":74,\"outFeatures\":75}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":378}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":116}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":346}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":74}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 128-feature user input and a 87-feature item input, each through its own 2-layer MLP tower ending at width 347, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-398\nComponents:\n - user_input (input) params={\"shape\":[1,128]}\n - item_input (input) params={\"shape\":[1,87]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,128]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,87]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":128,\"outFeatures\":347}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":347,\"outFeatures\":347}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":87,\"outFeatures\":347}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":347,\"outFeatures\":347}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":694,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (73-feature input, 31 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-399\nComponents:\n - input (input) params={\"shape\":[1,73]}\n - fc1 (linear) params={\"inFeatures\":73,\"outFeatures\":15}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":15,\"outFeatures\":15}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":15,\"outFeatures\":31}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":73,\"outFeatures\":802}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":802,\"outFeatures\":802}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":802,\"outFeatures\":31}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 103-feature input with 158 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-400\nComponents:\n - input (input) params={\"shape\":[1,103]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,103]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":103,\"outFeatures\":68}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":68,\"outFeatures\":103}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":103,\"outFeatures\":224}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":224,\"outFeatures\":804}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":804,\"outFeatures\":253}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":253,\"outFeatures\":158}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1642-dim input: encode down to a 255-dim bottleneck and decode back to 1642. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-401\nComponents:\n - input (input) params={\"shape\":[1,1642]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1642]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1642,\"outFeatures\":713}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":713,\"outFeatures\":255}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":255,\"outFeatures\":713}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":713,\"outFeatures\":1642}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x64x64 image with 48 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-402\nComponents:\n - input (input) params={\"shape\":[1,3,64,64]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,64,64]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":28,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":28,\"outChannels\":47,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":47,\"outChannels\":32,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":32,\"outChannels\":57,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":57,\"outFeatures\":48}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 323-token sequences with 51 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-403\nComponents:\n - input (input) params={\"shape\":[1,323]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,323]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":37585,\"embeddingDim\":104}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":104,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":104,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":104,\"outFeatures\":51}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 220-token sequences with 83 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-404\nComponents:\n - input (input) params={\"shape\":[1,220]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,220]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":9403,\"embeddingDim\":160}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":160,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[160]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":160,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[160]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":160,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[160]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":160,\"outFeatures\":83}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 2976-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-406\nComponents:\n - input (input) params={\"shape\":[1,247]}\n - fc1 (linear) params={\"inFeatures\":247,\"outFeatures\":2976}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2976,\"outFeatures\":2976}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":2976,\"outFeatures\":45}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":247,\"outFeatures\":230}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":230,\"outFeatures\":230}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":230,\"outFeatures\":45}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 146-feature, 10-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-407\nComponents:\n - input (input) params={\"shape\":[1,146]}\n - fc1 (linear) params={\"inFeatures\":146,\"outFeatures\":253}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":253,\"outFeatures\":69}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":69,\"outFeatures\":166}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":166,\"outFeatures\":10}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":253}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":69}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":166}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 22-feature user input and a 89-feature item input, each through its own 2-layer MLP tower ending at width 417, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-408\nComponents:\n - user_input (input) params={\"shape\":[1,22]}\n - item_input (input) params={\"shape\":[1,89]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,22]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,89]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":22,\"outFeatures\":417}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":417,\"outFeatures\":417}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":89,\"outFeatures\":417}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":417,\"outFeatures\":417}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":834,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (61-feature input, 40 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-409\nComponents:\n - input (input) params={\"shape\":[1,61]}\n - fc1 (linear) params={\"inFeatures\":61,\"outFeatures\":17}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":17,\"outFeatures\":17}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":17,\"outFeatures\":40}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":61,\"outFeatures\":877}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":877,\"outFeatures\":877}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":877,\"outFeatures\":40}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 31-feature input with 150 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-410\nComponents:\n - input (input) params={\"shape\":[1,31]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,31]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":31,\"outFeatures\":797}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":797,\"outFeatures\":309}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":309,\"outFeatures\":569}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":569,\"outFeatures\":150}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1136-dim input: encode down to a 105-dim bottleneck and decode back to 1136. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-411\nComponents:\n - input (input) params={\"shape\":[1,1136]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1136]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1136,\"outFeatures\":444}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":444,\"outFeatures\":105}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":105,\"outFeatures\":444}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":444,\"outFeatures\":1136}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x39x39 image with 31 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-412\nComponents:\n - input (input) params={\"shape\":[1,3,39,39]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,39,39]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":15,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":15,\"outChannels\":32,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":32,\"outChannels\":45,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":45,\"outFeatures\":31}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 303-token sequences with 74 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-413\nComponents:\n - input (input) params={\"shape\":[1,303]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,303]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":22288,\"embeddingDim\":24}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":24,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":24,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":24,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":24,\"outFeatures\":74}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 461-token sequences with 73 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-414\nComponents:\n - input (input) params={\"shape\":[1,461]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,461]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":42765,\"embeddingDim\":672}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":672,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[672]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":672,\"outFeatures\":73}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 2053-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-416\nComponents:\n - input (input) params={\"shape\":[1,142]}\n - fc1 (linear) params={\"inFeatures\":142,\"outFeatures\":2053}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2053,\"outFeatures\":2053}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2053,\"outFeatures\":2053}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":2053,\"outFeatures\":2053}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":2053,\"outFeatures\":14}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":142,\"outFeatures\":268}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":268,\"outFeatures\":268}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":268,\"outFeatures\":268}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":268,\"outFeatures\":268}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":268,\"outFeatures\":14}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 141-feature, 23-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-417\nComponents:\n - input (input) params={\"shape\":[1,141]}\n - fc1 (linear) params={\"inFeatures\":141,\"outFeatures\":112}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":112,\"outFeatures\":127}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":127,\"outFeatures\":415}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":415,\"outFeatures\":433}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":433,\"outFeatures\":23}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":112}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":127}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":415}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":433}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 115-feature user input and a 211-feature item input, each through its own 2-layer MLP tower ending at width 161, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-418\nComponents:\n - user_input (input) params={\"shape\":[1,115]}\n - item_input (input) params={\"shape\":[1,211]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,115]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,211]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":115,\"outFeatures\":161}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":161,\"outFeatures\":161}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":211,\"outFeatures\":161}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":161,\"outFeatures\":161}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":322,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (19-feature input, 24 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-419\nComponents:\n - input (input) params={\"shape\":[1,19]}\n - fc1 (linear) params={\"inFeatures\":19,\"outFeatures\":14}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":14,\"outFeatures\":14}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":14,\"outFeatures\":24}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":19,\"outFeatures\":1123}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1123,\"outFeatures\":1123}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1123,\"outFeatures\":24}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 321-feature input with 31 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-420\nComponents:\n - input (input) params={\"shape\":[1,321]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,321]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":321,\"outFeatures\":561}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":561,\"outFeatures\":854}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":854,\"outFeatures\":461}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":461,\"outFeatures\":47}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":47,\"outFeatures\":890}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":890,\"outFeatures\":31}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1098-dim input: encode down to a 33-dim bottleneck and decode back to 1098. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-421\nComponents:\n - input (input) params={\"shape\":[1,1098]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1098]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1098,\"outFeatures\":637}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":637,\"outFeatures\":33}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":33,\"outFeatures\":637}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":637,\"outFeatures\":1098}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x44x44 image with 75 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-422\nComponents:\n - input (input) params={\"shape\":[1,3,44,44]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,44,44]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":42,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":42,\"outChannels\":10,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":10,\"outFeatures\":75}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 465-token sequences with 28 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-423\nComponents:\n - input (input) params={\"shape\":[1,465]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,465]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":44266,\"embeddingDim\":176}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":176,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":176,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":176,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":176,\"outFeatures\":28}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 64-token sequences with 17 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-424\nComponents:\n - input (input) params={\"shape\":[1,64]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,64]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":34652,\"embeddingDim\":336}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":336,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[336]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":336,\"outFeatures\":17}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 2344-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-426\nComponents:\n - input (input) params={\"shape\":[1,237]}\n - fc1 (linear) params={\"inFeatures\":237,\"outFeatures\":2344}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2344,\"outFeatures\":2344}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2344,\"outFeatures\":2344}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":2344,\"outFeatures\":2344}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":2344,\"outFeatures\":17}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":237,\"outFeatures\":153}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":153,\"outFeatures\":153}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":153,\"outFeatures\":153}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":153,\"outFeatures\":153}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":153,\"outFeatures\":17}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 142-feature, 53-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-427\nComponents:\n - input (input) params={\"shape\":[1,142]}\n - fc1 (linear) params={\"inFeatures\":142,\"outFeatures\":177}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":177,\"outFeatures\":251}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":251,\"outFeatures\":102}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":102,\"outFeatures\":356}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":356,\"outFeatures\":53}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":177}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":251}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":102}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":356}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 167-feature user input and a 84-feature item input, each through its own 2-layer MLP tower ending at width 336, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-428\nComponents:\n - user_input (input) params={\"shape\":[1,167]}\n - item_input (input) params={\"shape\":[1,84]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,167]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,84]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":167,\"outFeatures\":336}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":336,\"outFeatures\":336}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":84,\"outFeatures\":336}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":336,\"outFeatures\":336}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":672,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (44-feature input, 31 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-429\nComponents:\n - input (input) params={\"shape\":[1,44]}\n - fc1 (linear) params={\"inFeatures\":44,\"outFeatures\":7}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":7,\"outFeatures\":7}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":7,\"outFeatures\":31}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":44,\"outFeatures\":699}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":699,\"outFeatures\":699}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":699,\"outFeatures\":31}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 415-feature input with 55 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-430\nComponents:\n - input (input) params={\"shape\":[1,415]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,415]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":415,\"outFeatures\":811}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":811,\"outFeatures\":587}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":587,\"outFeatures\":243}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":243,\"outFeatures\":890}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":890,\"outFeatures\":94}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":94,\"outFeatures\":363}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":363,\"outFeatures\":55}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 566-dim input: encode down to a 28-dim bottleneck and decode back to 566. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-431\nComponents:\n - input (input) params={\"shape\":[1,566]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,566]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":566,\"outFeatures\":126}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":126,\"outFeatures\":28}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":28,\"outFeatures\":126}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":126,\"outFeatures\":566}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x54x54 image with 84 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-432\nComponents:\n - input (input) params={\"shape\":[1,3,54,54]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,54,54]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":27,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":27,\"outChannels\":51,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":51,\"outChannels\":14,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":14,\"outFeatures\":84}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 254-token sequences with 85 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-433\nComponents:\n - input (input) params={\"shape\":[1,254]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,254]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":42584,\"embeddingDim\":156}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":156,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":156,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":156,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":156,\"outFeatures\":85}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 416-token sequences with 87 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-434\nComponents:\n - input (input) params={\"shape\":[1,416]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,416]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":48000,\"embeddingDim\":100}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":100,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[100]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":100,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[100]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":100,\"outFeatures\":87}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (148) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-435\nComponents:\n - input (input) params={\"shape\":[1,238]}\n - embed (embedding) params={\"numEmbeddings\":46439,\"embeddingDim\":148}\n - attn (multiHeadAttention) params={\"embedDim\":148,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":148,\"outFeatures\":33}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":4}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 2483-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-436\nComponents:\n - input (input) params={\"shape\":[1,200]}\n - fc1 (linear) params={\"inFeatures\":200,\"outFeatures\":2483}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2483,\"outFeatures\":2483}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2483,\"outFeatures\":2483}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":2483,\"outFeatures\":45}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":200,\"outFeatures\":108}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":108,\"outFeatures\":108}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":108,\"outFeatures\":108}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":108,\"outFeatures\":45}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 59-feature, 65-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-437\nComponents:\n - input (input) params={\"shape\":[1,59]}\n - fc1 (linear) params={\"inFeatures\":59,\"outFeatures\":194}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":194,\"outFeatures\":187}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":187,\"outFeatures\":65}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":194}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":187}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 175-feature user input and a 170-feature item input, each through its own 2-layer MLP tower ending at width 425, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-438\nComponents:\n - user_input (input) params={\"shape\":[1,175]}\n - item_input (input) params={\"shape\":[1,170]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,175]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,170]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":175,\"outFeatures\":425}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":425,\"outFeatures\":425}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":170,\"outFeatures\":425}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":425,\"outFeatures\":425}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":850,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (42-feature input, 35 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-439\nComponents:\n - input (input) params={\"shape\":[1,42]}\n - fc1 (linear) params={\"inFeatures\":42,\"outFeatures\":14}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":14,\"outFeatures\":14}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":14,\"outFeatures\":35}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":42,\"outFeatures\":898}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":898,\"outFeatures\":898}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":898,\"outFeatures\":35}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 206-feature input with 111 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-440\nComponents:\n - input (input) params={\"shape\":[1,206]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,206]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":206,\"outFeatures\":231}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":231,\"outFeatures\":542}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":542,\"outFeatures\":111}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 534-dim input: encode down to a 244-dim bottleneck and decode back to 534. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-441\nComponents:\n - input (input) params={\"shape\":[1,534]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,534]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":534,\"outFeatures\":833}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":833,\"outFeatures\":244}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":244,\"outFeatures\":833}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":833,\"outFeatures\":534}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x42x42 image with 34 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-442\nComponents:\n - input (input) params={\"shape\":[1,3,42,42]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,42,42]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":56,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":56,\"outChannels\":39,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":39,\"outChannels\":62,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":62,\"outFeatures\":34}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 161-token sequences with 64 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-443\nComponents:\n - input (input) params={\"shape\":[1,161]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,161]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":36438,\"embeddingDim\":88}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":88,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":88,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":88,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":88,\"outFeatures\":64}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 483-token sequences with 26 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-444\nComponents:\n - input (input) params={\"shape\":[1,483]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,483]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":42079,\"embeddingDim\":100}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":100,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[100]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":100,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[100]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":100,\"outFeatures\":26}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (114) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-445\nComponents:\n - input (input) params={\"shape\":[1,385]}\n - embed (embedding) params={\"numEmbeddings\":11447,\"embeddingDim\":114}\n - attn (multiHeadAttention) params={\"embedDim\":114,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":114,\"outFeatures\":20}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 1747-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-446\nComponents:\n - input (input) params={\"shape\":[1,86]}\n - fc1 (linear) params={\"inFeatures\":86,\"outFeatures\":1747}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":1747,\"outFeatures\":1747}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":1747,\"outFeatures\":10}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":86,\"outFeatures\":103}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":103,\"outFeatures\":103}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":103,\"outFeatures\":10}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 144-feature, 13-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-447\nComponents:\n - input (input) params={\"shape\":[1,144]}\n - fc1 (linear) params={\"inFeatures\":144,\"outFeatures\":500}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":500,\"outFeatures\":154}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":154,\"outFeatures\":339}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":339,\"outFeatures\":13}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":500}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":154}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":339}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 170-feature user input and a 35-feature item input, each through its own 2-layer MLP tower ending at width 364, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-448\nComponents:\n - user_input (input) params={\"shape\":[1,170]}\n - item_input (input) params={\"shape\":[1,35]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,170]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,35]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":170,\"outFeatures\":364}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":364,\"outFeatures\":364}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":35,\"outFeatures\":364}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":364,\"outFeatures\":364}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":728,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (108-feature input, 47 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-449\nComponents:\n - input (input) params={\"shape\":[1,108]}\n - fc1 (linear) params={\"inFeatures\":108,\"outFeatures\":17}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":17,\"outFeatures\":17}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":17,\"outFeatures\":47}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":108,\"outFeatures\":734}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":734,\"outFeatures\":734}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":734,\"outFeatures\":47}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 228-feature input with 10 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-450\nComponents:\n - input (input) params={\"shape\":[1,228]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,228]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":228,\"outFeatures\":666}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":666,\"outFeatures\":108}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":108,\"outFeatures\":844}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":844,\"outFeatures\":244}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":244,\"outFeatures\":366}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":366,\"outFeatures\":578}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":578,\"outFeatures\":10}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 2016-dim input: encode down to a 229-dim bottleneck and decode back to 2016. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-451\nComponents:\n - input (input) params={\"shape\":[1,2016]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,2016]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":2016,\"outFeatures\":389}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":389,\"outFeatures\":229}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":229,\"outFeatures\":389}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":389,\"outFeatures\":2016}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x39x39 image with 62 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-452\nComponents:\n - input (input) params={\"shape\":[1,3,39,39]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,39,39]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":48,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":48,\"outChannels\":64,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":64,\"outFeatures\":62}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 318-token sequences with 91 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-453\nComponents:\n - input (input) params={\"shape\":[1,318]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,318]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":38676,\"embeddingDim\":200}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":200,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":200,\"outFeatures\":91}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 102-token sequences with 37 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-454\nComponents:\n - input (input) params={\"shape\":[1,102]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,102]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":31902,\"embeddingDim\":160}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":160,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[160]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":160,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[160]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":160,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[160]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":160,\"outFeatures\":37}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (236) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-455\nComponents:\n - input (input) params={\"shape\":[1,65]}\n - embed (embedding) params={\"numEmbeddings\":26615,\"embeddingDim\":236}\n - attn (multiHeadAttention) params={\"embedDim\":236,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":236,\"outFeatures\":31}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":4}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3243-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-456\nComponents:\n - input (input) params={\"shape\":[1,39]}\n - fc1 (linear) params={\"inFeatures\":39,\"outFeatures\":3243}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3243,\"outFeatures\":3243}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3243,\"outFeatures\":3243}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3243,\"outFeatures\":3243}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3243,\"outFeatures\":24}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":39,\"outFeatures\":153}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":153,\"outFeatures\":153}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":153,\"outFeatures\":153}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":153,\"outFeatures\":153}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":153,\"outFeatures\":24}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 24-feature, 65-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-457\nComponents:\n - input (input) params={\"shape\":[1,24]}\n - fc1 (linear) params={\"inFeatures\":24,\"outFeatures\":346}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":346,\"outFeatures\":469}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":469,\"outFeatures\":457}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":457,\"outFeatures\":284}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":284,\"outFeatures\":394}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":394,\"outFeatures\":65}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":346}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":469}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":457}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":284}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":394}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 64-feature user input and a 256-feature item input, each through its own 2-layer MLP tower ending at width 407, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-458\nComponents:\n - user_input (input) params={\"shape\":[1,64]}\n - item_input (input) params={\"shape\":[1,256]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,64]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,256]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":64,\"outFeatures\":407}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":407,\"outFeatures\":407}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":256,\"outFeatures\":407}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":407,\"outFeatures\":407}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":814,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (72-feature input, 21 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-459\nComponents:\n - input (input) params={\"shape\":[1,72]}\n - fc1 (linear) params={\"inFeatures\":72,\"outFeatures\":9}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":9,\"outFeatures\":9}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":9,\"outFeatures\":21}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":72,\"outFeatures\":1149}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1149,\"outFeatures\":1149}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1149,\"outFeatures\":21}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 248-feature input with 20 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-460\nComponents:\n - input (input) params={\"shape\":[1,248]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,248]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":248,\"outFeatures\":247}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":247,\"outFeatures\":704}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":704,\"outFeatures\":622}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":622,\"outFeatures\":41}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":41,\"outFeatures\":159}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":159,\"outFeatures\":425}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":425,\"outFeatures\":20}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 2012-dim input: encode down to a 46-dim bottleneck and decode back to 2012. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-461\nComponents:\n - input (input) params={\"shape\":[1,2012]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,2012]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":2012,\"outFeatures\":331}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":331,\"outFeatures\":46}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":46,\"outFeatures\":331}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":331,\"outFeatures\":2012}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x38x38 image with 15 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-462\nComponents:\n - input (input) params={\"shape\":[1,3,38,38]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,38,38]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":47,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":47,\"outChannels\":38,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":38,\"outChannels\":34,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":34,\"outChannels\":37,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":37,\"outFeatures\":15}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 393-token sequences with 83 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-463\nComponents:\n - input (input) params={\"shape\":[1,393]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,393]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":33431,\"embeddingDim\":472}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":472,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":472,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":472,\"outFeatures\":83}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 235-token sequences with 57 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-464\nComponents:\n - input (input) params={\"shape\":[1,235]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,235]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":35301,\"embeddingDim\":208}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":208,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[208]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":208,\"outFeatures\":57}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (254) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-465\nComponents:\n - input (input) params={\"shape\":[1,253]}\n - embed (embedding) params={\"numEmbeddings\":37355,\"embeddingDim\":254}\n - attn (multiHeadAttention) params={\"embedDim\":254,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":254,\"outFeatures\":79}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 1979-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-466\nComponents:\n - input (input) params={\"shape\":[1,90]}\n - fc1 (linear) params={\"inFeatures\":90,\"outFeatures\":1979}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":1979,\"outFeatures\":1979}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":1979,\"outFeatures\":1979}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":1979,\"outFeatures\":45}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":90,\"outFeatures\":368}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":368,\"outFeatures\":368}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":368,\"outFeatures\":368}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":368,\"outFeatures\":45}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 106-feature, 33-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-467\nComponents:\n - input (input) params={\"shape\":[1,106]}\n - fc1 (linear) params={\"inFeatures\":106,\"outFeatures\":233}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":233,\"outFeatures\":287}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":287,\"outFeatures\":46}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":46,\"outFeatures\":33}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":233}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":287}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":46}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 141-feature user input and a 102-feature item input, each through its own 2-layer MLP tower ending at width 475, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-468\nComponents:\n - user_input (input) params={\"shape\":[1,141]}\n - item_input (input) params={\"shape\":[1,102]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,141]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,102]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":141,\"outFeatures\":475}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":475,\"outFeatures\":475}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":102,\"outFeatures\":475}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":475,\"outFeatures\":475}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":950,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (82-feature input, 21 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-469\nComponents:\n - input (input) params={\"shape\":[1,82]}\n - fc1 (linear) params={\"inFeatures\":82,\"outFeatures\":15}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":15,\"outFeatures\":15}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":15,\"outFeatures\":21}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":82,\"outFeatures\":1118}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1118,\"outFeatures\":1118}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1118,\"outFeatures\":21}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 163-feature input with 75 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-470\nComponents:\n - input (input) params={\"shape\":[1,163]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,163]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":163,\"outFeatures\":878}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":878,\"outFeatures\":317}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":317,\"outFeatures\":655}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":655,\"outFeatures\":440}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":440,\"outFeatures\":75}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 588-dim input: encode down to a 19-dim bottleneck and decode back to 588. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-471\nComponents:\n - input (input) params={\"shape\":[1,588]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,588]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":588,\"outFeatures\":416}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":416,\"outFeatures\":19}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":19,\"outFeatures\":416}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":416,\"outFeatures\":588}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x29x29 image with 22 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-472\nComponents:\n - input (input) params={\"shape\":[1,3,29,29]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,29,29]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":61,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":61,\"outChannels\":31,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":31,\"outChannels\":64,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":64,\"outFeatures\":22}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 235-token sequences with 91 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-473\nComponents:\n - input (input) params={\"shape\":[1,235]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,235]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":30233,\"embeddingDim\":80}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":80,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":80,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":80,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":80,\"outFeatures\":91}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 219-token sequences with 78 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-474\nComponents:\n - input (input) params={\"shape\":[1,219]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,219]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":15591,\"embeddingDim\":416}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":416,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[416]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":416,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[416]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":416,\"outFeatures\":78}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (458) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-475\nComponents:\n - input (input) params={\"shape\":[1,51]}\n - embed (embedding) params={\"numEmbeddings\":25207,\"embeddingDim\":458}\n - attn (multiHeadAttention) params={\"embedDim\":458,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":458,\"outFeatures\":50}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 1599-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-476\nComponents:\n - input (input) params={\"shape\":[1,244]}\n - fc1 (linear) params={\"inFeatures\":244,\"outFeatures\":1599}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":1599,\"outFeatures\":1599}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":1599,\"outFeatures\":35}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":244,\"outFeatures\":179}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":179,\"outFeatures\":179}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":179,\"outFeatures\":35}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 110-feature, 22-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-477\nComponents:\n - input (input) params={\"shape\":[1,110]}\n - fc1 (linear) params={\"inFeatures\":110,\"outFeatures\":455}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":455,\"outFeatures\":327}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":327,\"outFeatures\":167}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":167,\"outFeatures\":22}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":455}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":327}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":167}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 148-feature user input and a 153-feature item input, each through its own 2-layer MLP tower ending at width 94, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-478\nComponents:\n - user_input (input) params={\"shape\":[1,148]}\n - item_input (input) params={\"shape\":[1,153]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,148]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,153]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":148,\"outFeatures\":94}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":94,\"outFeatures\":94}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":153,\"outFeatures\":94}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":94,\"outFeatures\":94}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":188,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (49-feature input, 20 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-479\nComponents:\n - input (input) params={\"shape\":[1,49]}\n - fc1 (linear) params={\"inFeatures\":49,\"outFeatures\":5}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":5,\"outFeatures\":5}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":5,\"outFeatures\":20}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":49,\"outFeatures\":1309}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1309,\"outFeatures\":1309}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1309,\"outFeatures\":20}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 43-feature input with 101 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-480\nComponents:\n - input (input) params={\"shape\":[1,43]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,43]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":43,\"outFeatures\":787}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":787,\"outFeatures\":760}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":760,\"outFeatures\":466}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":466,\"outFeatures\":101}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 342-dim input: encode down to a 200-dim bottleneck and decode back to 342. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-481\nComponents:\n - input (input) params={\"shape\":[1,342]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,342]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":342,\"outFeatures\":1011}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":1011,\"outFeatures\":200}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":200,\"outFeatures\":1011}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":1011,\"outFeatures\":342}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x24x24 image with 29 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-482\nComponents:\n - input (input) params={\"shape\":[1,3,24,24]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,24,24]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":19,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":19,\"outChannels\":24,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":24,\"outFeatures\":29}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 202-token sequences with 87 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-483\nComponents:\n - input (input) params={\"shape\":[1,202]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,202]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":20604,\"embeddingDim\":58}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":58,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":58,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":58,\"outFeatures\":87}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 324-token sequences with 63 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-484\nComponents:\n - input (input) params={\"shape\":[1,324]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,324]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":15422,\"embeddingDim\":256}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":256,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[256]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":256,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[256]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":256,\"outFeatures\":63}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 2136-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-486\nComponents:\n - input (input) params={\"shape\":[1,108]}\n - fc1 (linear) params={\"inFeatures\":108,\"outFeatures\":2136}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2136,\"outFeatures\":2136}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2136,\"outFeatures\":2136}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":2136,\"outFeatures\":27}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":108,\"outFeatures\":112}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":112,\"outFeatures\":112}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":112,\"outFeatures\":112}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":112,\"outFeatures\":27}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 21-feature, 90-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-487\nComponents:\n - input (input) params={\"shape\":[1,21]}\n - fc1 (linear) params={\"inFeatures\":21,\"outFeatures\":241}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":241,\"outFeatures\":188}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":188,\"outFeatures\":324}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":324,\"outFeatures\":90}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":241}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":188}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":324}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 30-feature user input and a 28-feature item input, each through its own 2-layer MLP tower ending at width 446, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-488\nComponents:\n - user_input (input) params={\"shape\":[1,30]}\n - item_input (input) params={\"shape\":[1,28]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,30]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,28]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":30,\"outFeatures\":446}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":446,\"outFeatures\":446}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":28,\"outFeatures\":446}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":446,\"outFeatures\":446}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":892,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (76-feature input, 5 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-489\nComponents:\n - input (input) params={\"shape\":[1,76]}\n - fc1 (linear) params={\"inFeatures\":76,\"outFeatures\":11}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":11,\"outFeatures\":11}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":11,\"outFeatures\":5}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":76,\"outFeatures\":904}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":904,\"outFeatures\":904}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":904,\"outFeatures\":5}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 21-feature input with 4 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-490\nComponents:\n - input (input) params={\"shape\":[1,21]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,21]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":21,\"outFeatures\":1017}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1017,\"outFeatures\":147}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":147,\"outFeatures\":84}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":84,\"outFeatures\":116}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":116,\"outFeatures\":239}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":239,\"outFeatures\":690}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":690,\"outFeatures\":4}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 2034-dim input: encode down to a 183-dim bottleneck and decode back to 2034. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-491\nComponents:\n - input (input) params={\"shape\":[1,2034]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,2034]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":2034,\"outFeatures\":285}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":285,\"outFeatures\":183}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":183,\"outFeatures\":285}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":285,\"outFeatures\":2034}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x26x26 image with 66 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-492\nComponents:\n - input (input) params={\"shape\":[1,3,26,26]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,26,26]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":49,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":49,\"outChannels\":63,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":63,\"outChannels\":60,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":60,\"outChannels\":15,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":15,\"outFeatures\":66}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 409-token sequences with 3 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-493\nComponents:\n - input (input) params={\"shape\":[1,409]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,409]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":41397,\"embeddingDim\":40}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":40,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":40,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":40,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":40,\"outFeatures\":3}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 71-token sequences with 54 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-494\nComponents:\n - input (input) params={\"shape\":[1,71]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,71]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":25579,\"embeddingDim\":768}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":768,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[768]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":768,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[768]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":768,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[768]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":768,\"outFeatures\":54}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (218) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-495\nComponents:\n - input (input) params={\"shape\":[1,383]}\n - embed (embedding) params={\"numEmbeddings\":20823,\"embeddingDim\":218}\n - attn (multiHeadAttention) params={\"embedDim\":218,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":218,\"outFeatures\":58}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 1742-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-496\nComponents:\n - input (input) params={\"shape\":[1,190]}\n - fc1 (linear) params={\"inFeatures\":190,\"outFeatures\":1742}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":1742,\"outFeatures\":1742}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":1742,\"outFeatures\":1742}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":1742,\"outFeatures\":16}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":190,\"outFeatures\":94}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":94,\"outFeatures\":94}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":94,\"outFeatures\":94}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":94,\"outFeatures\":16}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 223-feature, 8-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-497\nComponents:\n - input (input) params={\"shape\":[1,223]}\n - fc1 (linear) params={\"inFeatures\":223,\"outFeatures\":238}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":238,\"outFeatures\":270}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":270,\"outFeatures\":351}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":351,\"outFeatures\":8}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":238}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":270}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":351}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 82-feature user input and a 243-feature item input, each through its own 2-layer MLP tower ending at width 479, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-498\nComponents:\n - user_input (input) params={\"shape\":[1,82]}\n - item_input (input) params={\"shape\":[1,243]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,82]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,243]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":82,\"outFeatures\":479}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":479,\"outFeatures\":479}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":243,\"outFeatures\":479}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":479,\"outFeatures\":479}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":958,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (44-feature input, 17 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-499\nComponents:\n - input (input) params={\"shape\":[1,44]}\n - fc1 (linear) params={\"inFeatures\":44,\"outFeatures\":23}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":23,\"outFeatures\":23}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":23,\"outFeatures\":17}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":44,\"outFeatures\":855}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":855,\"outFeatures\":855}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":855,\"outFeatures\":17}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 442-feature input with 116 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-500\nComponents:\n - input (input) params={\"shape\":[1,442]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,442]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":442,\"outFeatures\":128}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":128,\"outFeatures\":775}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":775,\"outFeatures\":431}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":431,\"outFeatures\":843}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":843,\"outFeatures\":189}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":189,\"outFeatures\":893}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":893,\"outFeatures\":116}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1229-dim input: encode down to a 160-dim bottleneck and decode back to 1229. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-501\nComponents:\n - input (input) params={\"shape\":[1,1229]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1229]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1229,\"outFeatures\":112}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":112,\"outFeatures\":160}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":160,\"outFeatures\":112}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":112,\"outFeatures\":1229}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x29x29 image with 98 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-502\nComponents:\n - input (input) params={\"shape\":[1,3,29,29]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,29,29]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":60,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":60,\"outChannels\":28,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":28,\"outFeatures\":98}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 332-token sequences with 8 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-503\nComponents:\n - input (input) params={\"shape\":[1,332]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,332]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":9750,\"embeddingDim\":232}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":232,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":232,\"outFeatures\":8}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 407-token sequences with 17 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-504\nComponents:\n - input (input) params={\"shape\":[1,407]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,407]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":42375,\"embeddingDim\":160}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":160,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[160]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":160,\"outFeatures\":17}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (448) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-505\nComponents:\n - input (input) params={\"shape\":[1,316]}\n - embed (embedding) params={\"numEmbeddings\":47077,\"embeddingDim\":448}\n - attn (multiHeadAttention) params={\"embedDim\":448,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":448,\"outFeatures\":68}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":16}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 2378-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-506\nComponents:\n - input (input) params={\"shape\":[1,123]}\n - fc1 (linear) params={\"inFeatures\":123,\"outFeatures\":2378}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2378,\"outFeatures\":2378}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2378,\"outFeatures\":2378}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":2378,\"outFeatures\":6}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":123,\"outFeatures\":187}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":187,\"outFeatures\":187}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":187,\"outFeatures\":187}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":187,\"outFeatures\":6}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 79-feature, 70-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-507\nComponents:\n - input (input) params={\"shape\":[1,79]}\n - fc1 (linear) params={\"inFeatures\":79,\"outFeatures\":466}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":466,\"outFeatures\":222}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":222,\"outFeatures\":187}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":187,\"outFeatures\":70}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":466}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":222}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":187}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 51-feature user input and a 254-feature item input, each through its own 2-layer MLP tower ending at width 261, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-508\nComponents:\n - user_input (input) params={\"shape\":[1,51]}\n - item_input (input) params={\"shape\":[1,254]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,51]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,254]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":51,\"outFeatures\":261}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":261,\"outFeatures\":261}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":254,\"outFeatures\":261}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":261,\"outFeatures\":261}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":522,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (126-feature input, 16 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-509\nComponents:\n - input (input) params={\"shape\":[1,126]}\n - fc1 (linear) params={\"inFeatures\":126,\"outFeatures\":22}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":22,\"outFeatures\":22}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":22,\"outFeatures\":16}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":126,\"outFeatures\":742}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":742,\"outFeatures\":742}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":742,\"outFeatures\":16}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 389-feature input with 13 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-510\nComponents:\n - input (input) params={\"shape\":[1,389]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,389]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":389,\"outFeatures\":671}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":671,\"outFeatures\":632}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":632,\"outFeatures\":389}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":389,\"outFeatures\":98}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":98,\"outFeatures\":575}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":575,\"outFeatures\":505}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":505,\"outFeatures\":13}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1357-dim input: encode down to a 20-dim bottleneck and decode back to 1357. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-511\nComponents:\n - input (input) params={\"shape\":[1,1357]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1357]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1357,\"outFeatures\":444}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":444,\"outFeatures\":20}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":20,\"outFeatures\":444}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":444,\"outFeatures\":1357}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x32x32 image with 92 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-512\nComponents:\n - input (input) params={\"shape\":[1,3,32,32]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,32,32]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":26,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":26,\"outChannels\":61,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":61,\"outFeatures\":92}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 402-token sequences with 13 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-513\nComponents:\n - input (input) params={\"shape\":[1,402]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,402]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":18781,\"embeddingDim\":104}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":104,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":104,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":104,\"outFeatures\":13}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 229-token sequences with 10 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-514\nComponents:\n - input (input) params={\"shape\":[1,229]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,229]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":41228,\"embeddingDim\":136}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":136,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[136]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":136,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[136]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":136,\"outFeatures\":10}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3024-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-516\nComponents:\n - input (input) params={\"shape\":[1,98]}\n - fc1 (linear) params={\"inFeatures\":98,\"outFeatures\":3024}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3024,\"outFeatures\":3024}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3024,\"outFeatures\":3024}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3024,\"outFeatures\":3024}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3024,\"outFeatures\":9}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":98,\"outFeatures\":114}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":114,\"outFeatures\":114}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":114,\"outFeatures\":114}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":114,\"outFeatures\":114}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":114,\"outFeatures\":9}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 76-feature, 42-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-517\nComponents:\n - input (input) params={\"shape\":[1,76]}\n - fc1 (linear) params={\"inFeatures\":76,\"outFeatures\":198}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":198,\"outFeatures\":452}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":452,\"outFeatures\":223}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":223,\"outFeatures\":430}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":430,\"outFeatures\":42}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":198}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":452}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":223}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":430}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 78-feature user input and a 91-feature item input, each through its own 2-layer MLP tower ending at width 132, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-518\nComponents:\n - user_input (input) params={\"shape\":[1,78]}\n - item_input (input) params={\"shape\":[1,91]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,78]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,91]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":78,\"outFeatures\":132}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":132,\"outFeatures\":132}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":91,\"outFeatures\":132}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":132,\"outFeatures\":132}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":264,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (116-feature input, 40 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-519\nComponents:\n - input (input) params={\"shape\":[1,116]}\n - fc1 (linear) params={\"inFeatures\":116,\"outFeatures\":12}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":12,\"outFeatures\":12}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":12,\"outFeatures\":40}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":116,\"outFeatures\":1323}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1323,\"outFeatures\":1323}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1323,\"outFeatures\":40}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 383-feature input with 138 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-520\nComponents:\n - input (input) params={\"shape\":[1,383]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,383]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":383,\"outFeatures\":553}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":553,\"outFeatures\":69}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":69,\"outFeatures\":138}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1389-dim input: encode down to a 62-dim bottleneck and decode back to 1389. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-521\nComponents:\n - input (input) params={\"shape\":[1,1389]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1389]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1389,\"outFeatures\":886}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":886,\"outFeatures\":62}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":62,\"outFeatures\":886}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":886,\"outFeatures\":1389}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x47x47 image with 32 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-522\nComponents:\n - input (input) params={\"shape\":[1,3,47,47]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,47,47]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":38,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":38,\"outChannels\":17,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":17,\"outChannels\":24,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":24,\"outChannels\":9,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":9,\"outFeatures\":32}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 165-token sequences with 78 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-523\nComponents:\n - input (input) params={\"shape\":[1,165]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,165]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":36285,\"embeddingDim\":90}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":90,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":90,\"outFeatures\":78}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 108-token sequences with 34 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-524\nComponents:\n - input (input) params={\"shape\":[1,108]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,108]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":23545,\"embeddingDim\":256}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":256,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[256]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":256,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[256]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":256,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[256]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":256,\"outFeatures\":34}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (464) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-525\nComponents:\n - input (input) params={\"shape\":[1,183]}\n - embed (embedding) params={\"numEmbeddings\":13174,\"embeddingDim\":464}\n - attn (multiHeadAttention) params={\"embedDim\":464,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":464,\"outFeatures\":47}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":16}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 2199-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-526\nComponents:\n - input (input) params={\"shape\":[1,236]}\n - fc1 (linear) params={\"inFeatures\":236,\"outFeatures\":2199}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2199,\"outFeatures\":2199}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2199,\"outFeatures\":2199}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":2199,\"outFeatures\":37}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":236,\"outFeatures\":99}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":99,\"outFeatures\":99}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":99,\"outFeatures\":99}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":99,\"outFeatures\":37}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 93-feature, 40-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-527\nComponents:\n - input (input) params={\"shape\":[1,93]}\n - fc1 (linear) params={\"inFeatures\":93,\"outFeatures\":42}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":42,\"outFeatures\":276}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":276,\"outFeatures\":437}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":437,\"outFeatures\":478}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":478,\"outFeatures\":477}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":477,\"outFeatures\":40}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":42}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":276}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":437}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":478}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":477}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 69-feature user input and a 106-feature item input, each through its own 2-layer MLP tower ending at width 114, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-528\nComponents:\n - user_input (input) params={\"shape\":[1,69]}\n - item_input (input) params={\"shape\":[1,106]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,69]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,106]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":69,\"outFeatures\":114}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":114,\"outFeatures\":114}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":106,\"outFeatures\":114}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":114,\"outFeatures\":114}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":228,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (95-feature input, 5 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-529\nComponents:\n - input (input) params={\"shape\":[1,95]}\n - fc1 (linear) params={\"inFeatures\":95,\"outFeatures\":15}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":15,\"outFeatures\":15}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":15,\"outFeatures\":5}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":95,\"outFeatures\":1344}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1344,\"outFeatures\":1344}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1344,\"outFeatures\":5}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 305-feature input with 80 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-530\nComponents:\n - input (input) params={\"shape\":[1,305]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,305]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":305,\"outFeatures\":448}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":448,\"outFeatures\":721}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":721,\"outFeatures\":989}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":989,\"outFeatures\":453}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":453,\"outFeatures\":80}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 2047-dim input: encode down to a 214-dim bottleneck and decode back to 2047. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-531\nComponents:\n - input (input) params={\"shape\":[1,2047]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,2047]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":2047,\"outFeatures\":506}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":506,\"outFeatures\":214}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":214,\"outFeatures\":506}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":506,\"outFeatures\":2047}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x33x33 image with 45 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-532\nComponents:\n - input (input) params={\"shape\":[1,3,33,33]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,33,33]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":56,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":56,\"outChannels\":54,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":54,\"outChannels\":31,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":31,\"outFeatures\":45}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 428-token sequences with 73 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-533\nComponents:\n - input (input) params={\"shape\":[1,428]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,428]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":14594,\"embeddingDim\":18}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":18,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":18,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":18,\"outFeatures\":73}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 109-token sequences with 86 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-534\nComponents:\n - input (input) params={\"shape\":[1,109]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,109]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":44277,\"embeddingDim\":656}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":656,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[656]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":656,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[656]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":656,\"outFeatures\":86}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 3659-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-536\nComponents:\n - input (input) params={\"shape\":[1,62]}\n - fc1 (linear) params={\"inFeatures\":62,\"outFeatures\":3659}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3659,\"outFeatures\":3659}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3659,\"outFeatures\":3659}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":3659,\"outFeatures\":46}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":62,\"outFeatures\":250}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":250,\"outFeatures\":250}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":250,\"outFeatures\":250}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":250,\"outFeatures\":46}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 42-feature, 95-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-537\nComponents:\n - input (input) params={\"shape\":[1,42]}\n - fc1 (linear) params={\"inFeatures\":42,\"outFeatures\":110}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":110,\"outFeatures\":277}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":277,\"outFeatures\":477}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":477,\"outFeatures\":420}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":420,\"outFeatures\":193}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":193,\"outFeatures\":95}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":110}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":277}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":477}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":420}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":193}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 30-feature user input and a 39-feature item input, each through its own 2-layer MLP tower ending at width 108, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-538\nComponents:\n - user_input (input) params={\"shape\":[1,30]}\n - item_input (input) params={\"shape\":[1,39]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,30]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,39]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":30,\"outFeatures\":108}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":108,\"outFeatures\":108}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":39,\"outFeatures\":108}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":108,\"outFeatures\":108}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":216,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (40-feature input, 30 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-539\nComponents:\n - input (input) params={\"shape\":[1,40]}\n - fc1 (linear) params={\"inFeatures\":40,\"outFeatures\":20}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":20,\"outFeatures\":20}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":20,\"outFeatures\":30}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":40,\"outFeatures\":696}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":696,\"outFeatures\":696}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":696,\"outFeatures\":30}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 357-feature input with 43 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-540\nComponents:\n - input (input) params={\"shape\":[1,357]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,357]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":357,\"outFeatures\":607}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":607,\"outFeatures\":1006}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":1006,\"outFeatures\":137}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":137,\"outFeatures\":908}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":908,\"outFeatures\":104}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":104,\"outFeatures\":398}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":398,\"outFeatures\":43}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 108-dim input: encode down to a 115-dim bottleneck and decode back to 108. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-541\nComponents:\n - input (input) params={\"shape\":[1,108]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,108]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":108,\"outFeatures\":684}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":684,\"outFeatures\":115}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":115,\"outFeatures\":684}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":684,\"outFeatures\":108}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x42x42 image with 59 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-542\nComponents:\n - input (input) params={\"shape\":[1,3,42,42]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,42,42]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":60,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":60,\"outChannels\":9,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":9,\"outChannels\":30,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":30,\"outFeatures\":59}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 149-token sequences with 60 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-543\nComponents:\n - input (input) params={\"shape\":[1,149]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,149]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":33799,\"embeddingDim\":208}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":208,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":208,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":208,\"outFeatures\":60}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 158-token sequences with 92 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-544\nComponents:\n - input (input) params={\"shape\":[1,158]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,158]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":10388,\"embeddingDim\":156}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":156,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[156]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":156,\"outFeatures\":92}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (206) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-545\nComponents:\n - input (input) params={\"shape\":[1,402]}\n - embed (embedding) params={\"numEmbeddings\":29382,\"embeddingDim\":206}\n - attn (multiHeadAttention) params={\"embedDim\":206,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":206,\"outFeatures\":61}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 2060-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-546\nComponents:\n - input (input) params={\"shape\":[1,174]}\n - fc1 (linear) params={\"inFeatures\":174,\"outFeatures\":2060}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2060,\"outFeatures\":2060}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2060,\"outFeatures\":2060}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":2060,\"outFeatures\":2060}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":2060,\"outFeatures\":26}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":174,\"outFeatures\":232}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":232,\"outFeatures\":232}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":232,\"outFeatures\":232}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":232,\"outFeatures\":232}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":232,\"outFeatures\":26}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 89-feature, 45-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-547\nComponents:\n - input (input) params={\"shape\":[1,89]}\n - fc1 (linear) params={\"inFeatures\":89,\"outFeatures\":139}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":139,\"outFeatures\":334}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":334,\"outFeatures\":45}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":139}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":334}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 74-feature user input and a 107-feature item input, each through its own 2-layer MLP tower ending at width 147, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-548\nComponents:\n - user_input (input) params={\"shape\":[1,74]}\n - item_input (input) params={\"shape\":[1,107]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,74]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,107]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":74,\"outFeatures\":147}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":147,\"outFeatures\":147}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":107,\"outFeatures\":147}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":147,\"outFeatures\":147}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":294,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (58-feature input, 24 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-549\nComponents:\n - input (input) params={\"shape\":[1,58]}\n - fc1 (linear) params={\"inFeatures\":58,\"outFeatures\":21}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":21,\"outFeatures\":21}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":21,\"outFeatures\":24}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":58,\"outFeatures\":947}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":947,\"outFeatures\":947}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":947,\"outFeatures\":24}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 389-feature input with 200 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-550\nComponents:\n - input (input) params={\"shape\":[1,389]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,389]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":389,\"outFeatures\":789}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":789,\"outFeatures\":894}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":894,\"outFeatures\":537}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":537,\"outFeatures\":157}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":157,\"outFeatures\":200}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 574-dim input: encode down to a 186-dim bottleneck and decode back to 574. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-551\nComponents:\n - input (input) params={\"shape\":[1,574]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,574]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":574,\"outFeatures\":471}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":471,\"outFeatures\":186}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":186,\"outFeatures\":471}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":471,\"outFeatures\":574}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x35x35 image with 91 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-552\nComponents:\n - input (input) params={\"shape\":[1,3,35,35]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,35,35]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":43,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":43,\"outChannels\":10,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":10,\"outChannels\":26,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":26,\"outFeatures\":91}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 234-token sequences with 80 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-553\nComponents:\n - input (input) params={\"shape\":[1,234]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,234]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":12373,\"embeddingDim\":488}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":488,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":488,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":488,\"outFeatures\":80}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 509-token sequences with 58 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-554\nComponents:\n - input (input) params={\"shape\":[1,509]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,509]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":41777,\"embeddingDim\":104}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":104,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[104]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":104,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[104]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":104,\"outFeatures\":58}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 3462-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-556\nComponents:\n - input (input) params={\"shape\":[1,179]}\n - fc1 (linear) params={\"inFeatures\":179,\"outFeatures\":3462}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3462,\"outFeatures\":3462}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3462,\"outFeatures\":3462}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":3462,\"outFeatures\":19}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":179,\"outFeatures\":311}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":311,\"outFeatures\":311}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":311,\"outFeatures\":311}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":311,\"outFeatures\":19}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 137-feature, 42-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-557\nComponents:\n - input (input) params={\"shape\":[1,137]}\n - fc1 (linear) params={\"inFeatures\":137,\"outFeatures\":216}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":216,\"outFeatures\":157}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":157,\"outFeatures\":42}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":216}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":157}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 205-feature user input and a 135-feature item input, each through its own 2-layer MLP tower ending at width 318, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-558\nComponents:\n - user_input (input) params={\"shape\":[1,205]}\n - item_input (input) params={\"shape\":[1,135]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,205]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,135]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":205,\"outFeatures\":318}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":318,\"outFeatures\":318}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":135,\"outFeatures\":318}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":318,\"outFeatures\":318}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":636,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (119-feature input, 24 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-559\nComponents:\n - input (input) params={\"shape\":[1,119]}\n - fc1 (linear) params={\"inFeatures\":119,\"outFeatures\":8}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":8,\"outFeatures\":8}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":8,\"outFeatures\":24}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":119,\"outFeatures\":746}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":746,\"outFeatures\":746}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":746,\"outFeatures\":24}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 126-feature input with 184 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-560\nComponents:\n - input (input) params={\"shape\":[1,126]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,126]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":126,\"outFeatures\":830}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":830,\"outFeatures\":491}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":491,\"outFeatures\":97}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":97,\"outFeatures\":184}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 302-dim input: encode down to a 71-dim bottleneck and decode back to 302. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-561\nComponents:\n - input (input) params={\"shape\":[1,302]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,302]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":302,\"outFeatures\":588}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":588,\"outFeatures\":71}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":71,\"outFeatures\":588}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":588,\"outFeatures\":302}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x44x44 image with 32 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-562\nComponents:\n - input (input) params={\"shape\":[1,3,44,44]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,44,44]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":10,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":10,\"outChannels\":30,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":30,\"outChannels\":53,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":53,\"outFeatures\":32}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 393-token sequences with 9 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-563\nComponents:\n - input (input) params={\"shape\":[1,393]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,393]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":24554,\"embeddingDim\":496}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":496,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":496,\"outFeatures\":9}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 292-token sequences with 15 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-564\nComponents:\n - input (input) params={\"shape\":[1,292]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,292]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":36502,\"embeddingDim\":76}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":76,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[76]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":76,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[76]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":76,\"outFeatures\":15}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3843-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-566\nComponents:\n - input (input) params={\"shape\":[1,248]}\n - fc1 (linear) params={\"inFeatures\":248,\"outFeatures\":3843}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3843,\"outFeatures\":3843}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3843,\"outFeatures\":3843}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3843,\"outFeatures\":3843}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3843,\"outFeatures\":21}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":248,\"outFeatures\":260}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":260,\"outFeatures\":260}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":260,\"outFeatures\":260}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":260,\"outFeatures\":260}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":260,\"outFeatures\":21}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 96-feature, 64-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-567\nComponents:\n - input (input) params={\"shape\":[1,96]}\n - fc1 (linear) params={\"inFeatures\":96,\"outFeatures\":279}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":279,\"outFeatures\":370}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":370,\"outFeatures\":96}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":96,\"outFeatures\":307}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":307,\"outFeatures\":338}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":338,\"outFeatures\":64}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":279}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":370}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":96}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":307}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":338}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 189-feature user input and a 57-feature item input, each through its own 2-layer MLP tower ending at width 492, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-568\nComponents:\n - user_input (input) params={\"shape\":[1,189]}\n - item_input (input) params={\"shape\":[1,57]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,189]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,57]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":189,\"outFeatures\":492}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":492,\"outFeatures\":492}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":57,\"outFeatures\":492}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":492,\"outFeatures\":492}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":984,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (79-feature input, 2 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-569\nComponents:\n - input (input) params={\"shape\":[1,79]}\n - fc1 (linear) params={\"inFeatures\":79,\"outFeatures\":21}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":21,\"outFeatures\":21}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":21,\"outFeatures\":2}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":79,\"outFeatures\":1049}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1049,\"outFeatures\":1049}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1049,\"outFeatures\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 202-feature input with 62 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-570\nComponents:\n - input (input) params={\"shape\":[1,202]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,202]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":202,\"outFeatures\":528}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":528,\"outFeatures\":79}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":79,\"outFeatures\":245}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":245,\"outFeatures\":496}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":496,\"outFeatures\":457}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":457,\"outFeatures\":62}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 332-dim input: encode down to a 103-dim bottleneck and decode back to 332. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-571\nComponents:\n - input (input) params={\"shape\":[1,332]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,332]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":332,\"outFeatures\":632}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":632,\"outFeatures\":103}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":103,\"outFeatures\":632}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":632,\"outFeatures\":332}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x56x56 image with 11 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-572\nComponents:\n - input (input) params={\"shape\":[1,3,56,56]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,56,56]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":44,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":44,\"outChannels\":10,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":10,\"outFeatures\":11}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 79-token sequences with 9 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-573\nComponents:\n - input (input) params={\"shape\":[1,79]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,79]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":33873,\"embeddingDim\":224}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":224,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":224,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":224,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":224,\"outFeatures\":9}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 70-token sequences with 13 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-574\nComponents:\n - input (input) params={\"shape\":[1,70]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,70]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":37922,\"embeddingDim\":144}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":144,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[144]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":144,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[144]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":144,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[144]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":144,\"outFeatures\":13}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 3472-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-576\nComponents:\n - input (input) params={\"shape\":[1,151]}\n - fc1 (linear) params={\"inFeatures\":151,\"outFeatures\":3472}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3472,\"outFeatures\":3472}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":3472,\"outFeatures\":15}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":151,\"outFeatures\":152}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":152,\"outFeatures\":152}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":152,\"outFeatures\":15}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 238-feature, 35-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-577\nComponents:\n - input (input) params={\"shape\":[1,238]}\n - fc1 (linear) params={\"inFeatures\":238,\"outFeatures\":218}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":218,\"outFeatures\":175}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":175,\"outFeatures\":35}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":218}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":175}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 52-feature user input and a 155-feature item input, each through its own 2-layer MLP tower ending at width 74, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-578\nComponents:\n - user_input (input) params={\"shape\":[1,52]}\n - item_input (input) params={\"shape\":[1,155]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,52]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,155]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":52,\"outFeatures\":74}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":74,\"outFeatures\":74}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":155,\"outFeatures\":74}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":74,\"outFeatures\":74}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":148,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (42-feature input, 31 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-579\nComponents:\n - input (input) params={\"shape\":[1,42]}\n - fc1 (linear) params={\"inFeatures\":42,\"outFeatures\":18}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":18,\"outFeatures\":18}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":18,\"outFeatures\":31}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":42,\"outFeatures\":691}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":691,\"outFeatures\":691}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":691,\"outFeatures\":31}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 496-feature input with 146 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-580\nComponents:\n - input (input) params={\"shape\":[1,496]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,496]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":496,\"outFeatures\":450}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":450,\"outFeatures\":593}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":593,\"outFeatures\":121}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":121,\"outFeatures\":428}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":428,\"outFeatures\":559}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":559,\"outFeatures\":146}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1310-dim input: encode down to a 28-dim bottleneck and decode back to 1310. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-581\nComponents:\n - input (input) params={\"shape\":[1,1310]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1310]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1310,\"outFeatures\":247}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":247,\"outFeatures\":28}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":28,\"outFeatures\":247}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":247,\"outFeatures\":1310}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x49x49 image with 40 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-582\nComponents:\n - input (input) params={\"shape\":[1,3,49,49]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,49,49]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":53,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":53,\"outChannels\":33,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":33,\"outChannels\":30,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":30,\"outFeatures\":40}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 347-token sequences with 81 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-583\nComponents:\n - input (input) params={\"shape\":[1,347]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,347]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":15825,\"embeddingDim\":464}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":464,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":464,\"outFeatures\":81}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 298-token sequences with 93 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-584\nComponents:\n - input (input) params={\"shape\":[1,298]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,298]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":42457,\"embeddingDim\":64}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":64,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[64]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":64,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[64]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":64,\"outFeatures\":93}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3570-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-586\nComponents:\n - input (input) params={\"shape\":[1,181]}\n - fc1 (linear) params={\"inFeatures\":181,\"outFeatures\":3570}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3570,\"outFeatures\":3570}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3570,\"outFeatures\":3570}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3570,\"outFeatures\":3570}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3570,\"outFeatures\":22}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":181,\"outFeatures\":291}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":291,\"outFeatures\":291}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":291,\"outFeatures\":291}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":291,\"outFeatures\":291}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":291,\"outFeatures\":22}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 116-feature, 69-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-587\nComponents:\n - input (input) params={\"shape\":[1,116]}\n - fc1 (linear) params={\"inFeatures\":116,\"outFeatures\":357}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":357,\"outFeatures\":440}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":440,\"outFeatures\":69}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":357}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":440}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 123-feature user input and a 69-feature item input, each through its own 2-layer MLP tower ending at width 199, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-588\nComponents:\n - user_input (input) params={\"shape\":[1,123]}\n - item_input (input) params={\"shape\":[1,69]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,123]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,69]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":123,\"outFeatures\":199}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":199,\"outFeatures\":199}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":69,\"outFeatures\":199}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":199,\"outFeatures\":199}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":398,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (62-feature input, 26 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-589\nComponents:\n - input (input) params={\"shape\":[1,62]}\n - fc1 (linear) params={\"inFeatures\":62,\"outFeatures\":18}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":18,\"outFeatures\":18}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":18,\"outFeatures\":26}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":62,\"outFeatures\":1129}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1129,\"outFeatures\":1129}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1129,\"outFeatures\":26}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 285-feature input with 54 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-590\nComponents:\n - input (input) params={\"shape\":[1,285]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,285]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":285,\"outFeatures\":182}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":182,\"outFeatures\":699}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":699,\"outFeatures\":204}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":204,\"outFeatures\":54}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1176-dim input: encode down to a 48-dim bottleneck and decode back to 1176. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-591\nComponents:\n - input (input) params={\"shape\":[1,1176]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1176]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1176,\"outFeatures\":408}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":408,\"outFeatures\":48}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":48,\"outFeatures\":408}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":408,\"outFeatures\":1176}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x49x49 image with 75 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-592\nComponents:\n - input (input) params={\"shape\":[1,3,49,49]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,49,49]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":15,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":15,\"outChannels\":25,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":25,\"outChannels\":34,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":34,\"outFeatures\":75}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 304-token sequences with 29 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-593\nComponents:\n - input (input) params={\"shape\":[1,304]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,304]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":38369,\"embeddingDim\":34}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":34,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":34,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":34,\"outFeatures\":29}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 394-token sequences with 68 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-594\nComponents:\n - input (input) params={\"shape\":[1,394]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,394]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":16433,\"embeddingDim\":320}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":320,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[320]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":320,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[320]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":320,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[320]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":320,\"outFeatures\":68}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 2674-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-596\nComponents:\n - input (input) params={\"shape\":[1,56]}\n - fc1 (linear) params={\"inFeatures\":56,\"outFeatures\":2674}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2674,\"outFeatures\":2674}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2674,\"outFeatures\":2674}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":2674,\"outFeatures\":2674}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":2674,\"outFeatures\":3}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":56,\"outFeatures\":279}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":279,\"outFeatures\":279}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":279,\"outFeatures\":279}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":279,\"outFeatures\":279}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":279,\"outFeatures\":3}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 103-feature, 33-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-597\nComponents:\n - input (input) params={\"shape\":[1,103]}\n - fc1 (linear) params={\"inFeatures\":103,\"outFeatures\":63}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":63,\"outFeatures\":322}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":322,\"outFeatures\":506}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":506,\"outFeatures\":33}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":63}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":322}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":506}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 189-feature user input and a 178-feature item input, each through its own 2-layer MLP tower ending at width 312, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-598\nComponents:\n - user_input (input) params={\"shape\":[1,189]}\n - item_input (input) params={\"shape\":[1,178]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,189]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,178]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":189,\"outFeatures\":312}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":312,\"outFeatures\":312}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":178,\"outFeatures\":312}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":312,\"outFeatures\":312}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":624,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (83-feature input, 34 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-599\nComponents:\n - input (input) params={\"shape\":[1,83]}\n - fc1 (linear) params={\"inFeatures\":83,\"outFeatures\":19}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":19,\"outFeatures\":19}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":19,\"outFeatures\":34}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":83,\"outFeatures\":1240}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1240,\"outFeatures\":1240}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1240,\"outFeatures\":34}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 41-feature input with 82 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-600\nComponents:\n - input (input) params={\"shape\":[1,41]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,41]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":41,\"outFeatures\":494}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":494,\"outFeatures\":229}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":229,\"outFeatures\":962}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":962,\"outFeatures\":82}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1804-dim input: encode down to a 76-dim bottleneck and decode back to 1804. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-601\nComponents:\n - input (input) params={\"shape\":[1,1804]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1804]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1804,\"outFeatures\":653}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":653,\"outFeatures\":76}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":76,\"outFeatures\":653}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":653,\"outFeatures\":1804}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x35x35 image with 57 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-602\nComponents:\n - input (input) params={\"shape\":[1,3,35,35]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,35,35]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":25,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":25,\"outChannels\":17,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":17,\"outChannels\":20,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":20,\"outFeatures\":57}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 185-token sequences with 13 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-603\nComponents:\n - input (input) params={\"shape\":[1,185]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,185]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":25664,\"embeddingDim\":360}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":360,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":360,\"outFeatures\":13}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 82-token sequences with 25 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-604\nComponents:\n - input (input) params={\"shape\":[1,82]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,82]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":47477,\"embeddingDim\":232}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":232,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[232]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":232,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[232]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":232,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[232]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":232,\"outFeatures\":25}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 2147-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-606\nComponents:\n - input (input) params={\"shape\":[1,226]}\n - fc1 (linear) params={\"inFeatures\":226,\"outFeatures\":2147}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2147,\"outFeatures\":2147}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2147,\"outFeatures\":2147}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":2147,\"outFeatures\":2147}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":2147,\"outFeatures\":35}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":226,\"outFeatures\":118}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":118,\"outFeatures\":118}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":118,\"outFeatures\":118}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":118,\"outFeatures\":118}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":118,\"outFeatures\":35}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 96-feature, 97-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-607\nComponents:\n - input (input) params={\"shape\":[1,96]}\n - fc1 (linear) params={\"inFeatures\":96,\"outFeatures\":32}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":32,\"outFeatures\":176}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":176,\"outFeatures\":255}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":255,\"outFeatures\":168}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":168,\"outFeatures\":97}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":32}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":176}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":255}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":168}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 171-feature user input and a 173-feature item input, each through its own 2-layer MLP tower ending at width 405, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-608\nComponents:\n - user_input (input) params={\"shape\":[1,171]}\n - item_input (input) params={\"shape\":[1,173]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,171]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,173]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":171,\"outFeatures\":405}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":405,\"outFeatures\":405}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":173,\"outFeatures\":405}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":405,\"outFeatures\":405}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":810,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (122-feature input, 22 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-609\nComponents:\n - input (input) params={\"shape\":[1,122]}\n - fc1 (linear) params={\"inFeatures\":122,\"outFeatures\":18}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":18,\"outFeatures\":18}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":18,\"outFeatures\":22}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":122,\"outFeatures\":1322}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1322,\"outFeatures\":1322}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1322,\"outFeatures\":22}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 210-feature input with 164 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-610\nComponents:\n - input (input) params={\"shape\":[1,210]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,210]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":210,\"outFeatures\":958}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":958,\"outFeatures\":356}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":356,\"outFeatures\":79}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":79,\"outFeatures\":62}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":62,\"outFeatures\":703}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":703,\"outFeatures\":164}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1857-dim input: encode down to a 234-dim bottleneck and decode back to 1857. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-611\nComponents:\n - input (input) params={\"shape\":[1,1857]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1857]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1857,\"outFeatures\":669}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":669,\"outFeatures\":234}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":234,\"outFeatures\":669}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":669,\"outFeatures\":1857}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x35x35 image with 47 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-612\nComponents:\n - input (input) params={\"shape\":[1,3,35,35]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,35,35]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":63,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":63,\"outChannels\":9,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":9,\"outFeatures\":47}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 168-token sequences with 96 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-613\nComponents:\n - input (input) params={\"shape\":[1,168]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,168]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":34244,\"embeddingDim\":352}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":352,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":352,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":352,\"outFeatures\":96}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 194-token sequences with 34 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-614\nComponents:\n - input (input) params={\"shape\":[1,194]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,194]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":16961,\"embeddingDim\":184}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":184,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[184]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":184,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[184]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":184,\"outFeatures\":34}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 3396-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-616\nComponents:\n - input (input) params={\"shape\":[1,189]}\n - fc1 (linear) params={\"inFeatures\":189,\"outFeatures\":3396}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3396,\"outFeatures\":3396}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":3396,\"outFeatures\":47}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":189,\"outFeatures\":138}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":138,\"outFeatures\":138}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":138,\"outFeatures\":47}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 224-feature, 28-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-617\nComponents:\n - input (input) params={\"shape\":[1,224]}\n - fc1 (linear) params={\"inFeatures\":224,\"outFeatures\":495}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":495,\"outFeatures\":396}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":396,\"outFeatures\":369}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":369,\"outFeatures\":215}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":215,\"outFeatures\":176}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":176,\"outFeatures\":28}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":495}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":396}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":369}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":215}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":176}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 167-feature user input and a 142-feature item input, each through its own 2-layer MLP tower ending at width 325, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-618\nComponents:\n - user_input (input) params={\"shape\":[1,167]}\n - item_input (input) params={\"shape\":[1,142]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,167]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,142]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":167,\"outFeatures\":325}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":325,\"outFeatures\":325}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":142,\"outFeatures\":325}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":325,\"outFeatures\":325}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":650,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (42-feature input, 37 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-619\nComponents:\n - input (input) params={\"shape\":[1,42]}\n - fc1 (linear) params={\"inFeatures\":42,\"outFeatures\":16}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":16,\"outFeatures\":16}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":16,\"outFeatures\":37}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":42,\"outFeatures\":976}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":976,\"outFeatures\":976}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":976,\"outFeatures\":37}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 369-feature input with 143 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-620\nComponents:\n - input (input) params={\"shape\":[1,369]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,369]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":369,\"outFeatures\":887}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":887,\"outFeatures\":877}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":877,\"outFeatures\":143}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1333-dim input: encode down to a 160-dim bottleneck and decode back to 1333. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-621\nComponents:\n - input (input) params={\"shape\":[1,1333]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1333]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1333,\"outFeatures\":361}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":361,\"outFeatures\":160}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":160,\"outFeatures\":361}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":361,\"outFeatures\":1333}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x50x50 image with 28 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-622\nComponents:\n - input (input) params={\"shape\":[1,3,50,50]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,50,50]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":22,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":22,\"outChannels\":30,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":30,\"outChannels\":33,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":33,\"outChannels\":26,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":26,\"outFeatures\":28}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 187-token sequences with 31 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-623\nComponents:\n - input (input) params={\"shape\":[1,187]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,187]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":22511,\"embeddingDim\":192}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":192,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":192,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":192,\"outFeatures\":31}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 203-token sequences with 75 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-624\nComponents:\n - input (input) params={\"shape\":[1,203]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,203]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":36541,\"embeddingDim\":384}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":384,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[384]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":384,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[384]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":384,\"outFeatures\":75}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 3925-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-626\nComponents:\n - input (input) params={\"shape\":[1,48]}\n - fc1 (linear) params={\"inFeatures\":48,\"outFeatures\":3925}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3925,\"outFeatures\":3925}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":3925,\"outFeatures\":41}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":48,\"outFeatures\":212}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":212,\"outFeatures\":212}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":212,\"outFeatures\":41}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 178-feature, 61-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-627\nComponents:\n - input (input) params={\"shape\":[1,178]}\n - fc1 (linear) params={\"inFeatures\":178,\"outFeatures\":32}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":32,\"outFeatures\":278}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":278,\"outFeatures\":258}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":258,\"outFeatures\":246}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":246,\"outFeatures\":61}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":32}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":278}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":258}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":246}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 244-feature user input and a 16-feature item input, each through its own 2-layer MLP tower ending at width 440, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-628\nComponents:\n - user_input (input) params={\"shape\":[1,244]}\n - item_input (input) params={\"shape\":[1,16]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,244]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,16]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":244,\"outFeatures\":440}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":440,\"outFeatures\":440}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":16,\"outFeatures\":440}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":440,\"outFeatures\":440}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":880,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (66-feature input, 25 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-629\nComponents:\n - input (input) params={\"shape\":[1,66]}\n - fc1 (linear) params={\"inFeatures\":66,\"outFeatures\":20}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":20,\"outFeatures\":20}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":20,\"outFeatures\":25}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":66,\"outFeatures\":979}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":979,\"outFeatures\":979}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":979,\"outFeatures\":25}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 133-feature input with 110 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-630\nComponents:\n - input (input) params={\"shape\":[1,133]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,133]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":133,\"outFeatures\":131}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":131,\"outFeatures\":302}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":302,\"outFeatures\":1008}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":1008,\"outFeatures\":529}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":529,\"outFeatures\":533}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":533,\"outFeatures\":110}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 188-dim input: encode down to a 168-dim bottleneck and decode back to 188. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-631\nComponents:\n - input (input) params={\"shape\":[1,188]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,188]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":188,\"outFeatures\":309}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":309,\"outFeatures\":168}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":168,\"outFeatures\":309}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":309,\"outFeatures\":188}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x47x47 image with 93 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-632\nComponents:\n - input (input) params={\"shape\":[1,3,47,47]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,47,47]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":64,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":64,\"outChannels\":48,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":48,\"outChannels\":38,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":38,\"outChannels\":58,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":58,\"outFeatures\":93}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 165-token sequences with 7 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-633\nComponents:\n - input (input) params={\"shape\":[1,165]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,165]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":42721,\"embeddingDim\":70}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":70,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":70,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":70,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":70,\"outFeatures\":7}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 62-token sequences with 73 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-634\nComponents:\n - input (input) params={\"shape\":[1,62]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,62]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":8199,\"embeddingDim\":128}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":128,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[128]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":128,\"outFeatures\":73}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 2394-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-636\nComponents:\n - input (input) params={\"shape\":[1,32]}\n - fc1 (linear) params={\"inFeatures\":32,\"outFeatures\":2394}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2394,\"outFeatures\":2394}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":2394,\"outFeatures\":19}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":32,\"outFeatures\":381}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":381,\"outFeatures\":381}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":381,\"outFeatures\":19}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 217-feature, 10-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-637\nComponents:\n - input (input) params={\"shape\":[1,217]}\n - fc1 (linear) params={\"inFeatures\":217,\"outFeatures\":175}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":175,\"outFeatures\":283}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":283,\"outFeatures\":440}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":440,\"outFeatures\":410}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":410,\"outFeatures\":10}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":175}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":283}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":440}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":410}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 220-feature user input and a 184-feature item input, each through its own 2-layer MLP tower ending at width 449, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-638\nComponents:\n - user_input (input) params={\"shape\":[1,220]}\n - item_input (input) params={\"shape\":[1,184]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,220]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,184]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":220,\"outFeatures\":449}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":449,\"outFeatures\":449}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":184,\"outFeatures\":449}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":449,\"outFeatures\":449}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":898,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (50-feature input, 22 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-639\nComponents:\n - input (input) params={\"shape\":[1,50]}\n - fc1 (linear) params={\"inFeatures\":50,\"outFeatures\":19}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":19,\"outFeatures\":19}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":19,\"outFeatures\":22}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":50,\"outFeatures\":853}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":853,\"outFeatures\":853}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":853,\"outFeatures\":22}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 388-feature input with 90 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-640\nComponents:\n - input (input) params={\"shape\":[1,388]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,388]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":388,\"outFeatures\":629}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":629,\"outFeatures\":460}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":460,\"outFeatures\":512}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":512,\"outFeatures\":73}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":73,\"outFeatures\":90}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 956-dim input: encode down to a 81-dim bottleneck and decode back to 956. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-641\nComponents:\n - input (input) params={\"shape\":[1,956]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,956]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":956,\"outFeatures\":928}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":928,\"outFeatures\":81}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":81,\"outFeatures\":928}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":928,\"outFeatures\":956}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x53x53 image with 39 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-642\nComponents:\n - input (input) params={\"shape\":[1,3,53,53]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,53,53]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":63,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":63,\"outChannels\":38,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":38,\"outChannels\":61,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":61,\"outChannels\":22,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":22,\"outFeatures\":39}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 298-token sequences with 63 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-643\nComponents:\n - input (input) params={\"shape\":[1,298]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,298]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":49725,\"embeddingDim\":66}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":66,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":66,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":66,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":66,\"outFeatures\":63}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 352-token sequences with 29 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-644\nComponents:\n - input (input) params={\"shape\":[1,352]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,352]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":23467,\"embeddingDim\":288}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":288,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[288]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":288,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[288]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":288,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[288]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":288,\"outFeatures\":29}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (368) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-645\nComponents:\n - input (input) params={\"shape\":[1,455]}\n - embed (embedding) params={\"numEmbeddings\":38126,\"embeddingDim\":368}\n - attn (multiHeadAttention) params={\"embedDim\":368,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":368,\"outFeatures\":8}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":16}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 3952-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-646\nComponents:\n - input (input) params={\"shape\":[1,65]}\n - fc1 (linear) params={\"inFeatures\":65,\"outFeatures\":3952}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3952,\"outFeatures\":3952}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":3952,\"outFeatures\":7}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":65,\"outFeatures\":148}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":148,\"outFeatures\":148}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":148,\"outFeatures\":7}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 103-feature, 43-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-647\nComponents:\n - input (input) params={\"shape\":[1,103]}\n - fc1 (linear) params={\"inFeatures\":103,\"outFeatures\":259}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":259,\"outFeatures\":125}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":125,\"outFeatures\":452}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":452,\"outFeatures\":384}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":384,\"outFeatures\":43}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":259}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":125}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":452}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":384}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 86-feature user input and a 109-feature item input, each through its own 2-layer MLP tower ending at width 473, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-648\nComponents:\n - user_input (input) params={\"shape\":[1,86]}\n - item_input (input) params={\"shape\":[1,109]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,86]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,109]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":86,\"outFeatures\":473}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":473,\"outFeatures\":473}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":109,\"outFeatures\":473}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":473,\"outFeatures\":473}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":946,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (108-feature input, 46 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-649\nComponents:\n - input (input) params={\"shape\":[1,108]}\n - fc1 (linear) params={\"inFeatures\":108,\"outFeatures\":10}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":10,\"outFeatures\":10}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":10,\"outFeatures\":46}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":108,\"outFeatures\":727}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":727,\"outFeatures\":727}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":727,\"outFeatures\":46}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 237-feature input with 39 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-650\nComponents:\n - input (input) params={\"shape\":[1,237]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,237]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":237,\"outFeatures\":494}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":494,\"outFeatures\":287}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":287,\"outFeatures\":241}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":241,\"outFeatures\":68}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":68,\"outFeatures\":39}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 101-dim input: encode down to a 98-dim bottleneck and decode back to 101. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-651\nComponents:\n - input (input) params={\"shape\":[1,101]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,101]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":101,\"outFeatures\":326}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":326,\"outFeatures\":98}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":98,\"outFeatures\":326}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":326,\"outFeatures\":101}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x28x28 image with 19 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-652\nComponents:\n - input (input) params={\"shape\":[1,3,28,28]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,28,28]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":38,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":38,\"outChannels\":38,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":38,\"outFeatures\":19}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 110-token sequences with 41 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-653\nComponents:\n - input (input) params={\"shape\":[1,110]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,110]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":42688,\"embeddingDim\":120}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":120,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":120,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":120,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":120,\"outFeatures\":41}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 511-token sequences with 34 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-654\nComponents:\n - input (input) params={\"shape\":[1,511]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,511]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":31275,\"embeddingDim\":104}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":104,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[104]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":104,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[104]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":104,\"outFeatures\":34}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (268) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-655\nComponents:\n - input (input) params={\"shape\":[1,154]}\n - embed (embedding) params={\"numEmbeddings\":18770,\"embeddingDim\":268}\n - attn (multiHeadAttention) params={\"embedDim\":268,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":268,\"outFeatures\":8}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":4}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 2419-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-656\nComponents:\n - input (input) params={\"shape\":[1,216]}\n - fc1 (linear) params={\"inFeatures\":216,\"outFeatures\":2419}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2419,\"outFeatures\":2419}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2419,\"outFeatures\":2419}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":2419,\"outFeatures\":9}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":216,\"outFeatures\":380}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":380,\"outFeatures\":380}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":380,\"outFeatures\":380}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":380,\"outFeatures\":9}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 29-feature, 96-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-657\nComponents:\n - input (input) params={\"shape\":[1,29]}\n - fc1 (linear) params={\"inFeatures\":29,\"outFeatures\":60}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":60,\"outFeatures\":139}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":139,\"outFeatures\":96}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":60}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":139}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 256-feature user input and a 246-feature item input, each through its own 2-layer MLP tower ending at width 253, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-658\nComponents:\n - user_input (input) params={\"shape\":[1,256]}\n - item_input (input) params={\"shape\":[1,246]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,256]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,246]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":256,\"outFeatures\":253}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":253,\"outFeatures\":253}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":246,\"outFeatures\":253}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":253,\"outFeatures\":253}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":506,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (33-feature input, 5 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-659\nComponents:\n - input (input) params={\"shape\":[1,33]}\n - fc1 (linear) params={\"inFeatures\":33,\"outFeatures\":19}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":19,\"outFeatures\":19}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":19,\"outFeatures\":5}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":33,\"outFeatures\":651}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":651,\"outFeatures\":651}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":651,\"outFeatures\":5}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 369-feature input with 32 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-660\nComponents:\n - input (input) params={\"shape\":[1,369]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,369]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":369,\"outFeatures\":147}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":147,\"outFeatures\":24}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":24,\"outFeatures\":771}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":771,\"outFeatures\":18}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":18,\"outFeatures\":32}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 221-dim input: encode down to a 46-dim bottleneck and decode back to 221. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-661\nComponents:\n - input (input) params={\"shape\":[1,221]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,221]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":221,\"outFeatures\":632}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":632,\"outFeatures\":46}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":46,\"outFeatures\":632}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":632,\"outFeatures\":221}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x40x40 image with 63 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-662\nComponents:\n - input (input) params={\"shape\":[1,3,40,40]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,40,40]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":45,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":45,\"outChannels\":48,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":48,\"outChannels\":38,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":38,\"outFeatures\":63}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 52-token sequences with 97 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-663\nComponents:\n - input (input) params={\"shape\":[1,52]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,52]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":27947,\"embeddingDim\":208}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":208,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":208,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":208,\"outFeatures\":97}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 155-token sequences with 93 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-664\nComponents:\n - input (input) params={\"shape\":[1,155]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,155]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":22197,\"embeddingDim\":192}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":192,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[192]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":192,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[192]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":192,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[192]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":192,\"outFeatures\":93}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3321-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-666\nComponents:\n - input (input) params={\"shape\":[1,35]}\n - fc1 (linear) params={\"inFeatures\":35,\"outFeatures\":3321}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3321,\"outFeatures\":3321}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3321,\"outFeatures\":3321}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3321,\"outFeatures\":3321}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3321,\"outFeatures\":14}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":35,\"outFeatures\":184}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":184,\"outFeatures\":184}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":184,\"outFeatures\":184}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":184,\"outFeatures\":184}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":184,\"outFeatures\":14}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 243-feature, 15-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-667\nComponents:\n - input (input) params={\"shape\":[1,243]}\n - fc1 (linear) params={\"inFeatures\":243,\"outFeatures\":171}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":171,\"outFeatures\":444}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":444,\"outFeatures\":199}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":199,\"outFeatures\":15}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":171}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":444}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":199}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 138-feature user input and a 161-feature item input, each through its own 2-layer MLP tower ending at width 431, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-668\nComponents:\n - user_input (input) params={\"shape\":[1,138]}\n - item_input (input) params={\"shape\":[1,161]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,138]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,161]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":138,\"outFeatures\":431}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":431,\"outFeatures\":431}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":161,\"outFeatures\":431}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":431,\"outFeatures\":431}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":862,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (87-feature input, 38 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-669\nComponents:\n - input (input) params={\"shape\":[1,87]}\n - fc1 (linear) params={\"inFeatures\":87,\"outFeatures\":12}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":12,\"outFeatures\":12}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":12,\"outFeatures\":38}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":87,\"outFeatures\":1127}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1127,\"outFeatures\":1127}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1127,\"outFeatures\":38}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 63-feature input with 192 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-670\nComponents:\n - input (input) params={\"shape\":[1,63]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,63]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":63,\"outFeatures\":938}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":938,\"outFeatures\":1019}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":1019,\"outFeatures\":757}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":757,\"outFeatures\":65}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":65,\"outFeatures\":192}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 124-dim input: encode down to a 220-dim bottleneck and decode back to 124. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-671\nComponents:\n - input (input) params={\"shape\":[1,124]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,124]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":124,\"outFeatures\":845}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":845,\"outFeatures\":220}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":220,\"outFeatures\":845}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":845,\"outFeatures\":124}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x35x35 image with 13 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-672\nComponents:\n - input (input) params={\"shape\":[1,3,35,35]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,35,35]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":56,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":56,\"outChannels\":34,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":34,\"outChannels\":26,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":26,\"outChannels\":45,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":45,\"outFeatures\":13}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 416-token sequences with 2 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-673\nComponents:\n - input (input) params={\"shape\":[1,416]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,416]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":15788,\"embeddingDim\":272}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":272,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":272,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":272,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":272,\"outFeatures\":2}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 512-token sequences with 76 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-674\nComponents:\n - input (input) params={\"shape\":[1,512]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,512]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":31923,\"embeddingDim\":264}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":264,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[264]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":264,\"outFeatures\":76}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (306) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-675\nComponents:\n - input (input) params={\"shape\":[1,422]}\n - embed (embedding) params={\"numEmbeddings\":12925,\"embeddingDim\":306}\n - attn (multiHeadAttention) params={\"embedDim\":306,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":306,\"outFeatures\":47}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 4018-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-676\nComponents:\n - input (input) params={\"shape\":[1,51]}\n - fc1 (linear) params={\"inFeatures\":51,\"outFeatures\":4018}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":4018,\"outFeatures\":4018}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":4018,\"outFeatures\":46}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":51,\"outFeatures\":371}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":371,\"outFeatures\":371}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":371,\"outFeatures\":46}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 209-feature, 26-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-677\nComponents:\n - input (input) params={\"shape\":[1,209]}\n - fc1 (linear) params={\"inFeatures\":209,\"outFeatures\":352}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":352,\"outFeatures\":375}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":375,\"outFeatures\":26}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":352}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":375}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 93-feature user input and a 204-feature item input, each through its own 2-layer MLP tower ending at width 510, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-678\nComponents:\n - user_input (input) params={\"shape\":[1,93]}\n - item_input (input) params={\"shape\":[1,204]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,93]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,204]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":93,\"outFeatures\":510}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":510,\"outFeatures\":510}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":204,\"outFeatures\":510}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":510,\"outFeatures\":510}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":1020,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (121-feature input, 15 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-679\nComponents:\n - input (input) params={\"shape\":[1,121]}\n - fc1 (linear) params={\"inFeatures\":121,\"outFeatures\":13}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":13,\"outFeatures\":13}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":13,\"outFeatures\":15}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":121,\"outFeatures\":1011}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1011,\"outFeatures\":1011}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1011,\"outFeatures\":15}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 369-feature input with 160 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-680\nComponents:\n - input (input) params={\"shape\":[1,369]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,369]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":369,\"outFeatures\":692}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":692,\"outFeatures\":215}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":215,\"outFeatures\":664}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":664,\"outFeatures\":594}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":594,\"outFeatures\":75}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":75,\"outFeatures\":225}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":225,\"outFeatures\":160}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 111-dim input: encode down to a 17-dim bottleneck and decode back to 111. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-681\nComponents:\n - input (input) params={\"shape\":[1,111]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,111]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":111,\"outFeatures\":796}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":796,\"outFeatures\":17}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":17,\"outFeatures\":796}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":796,\"outFeatures\":111}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x44x44 image with 28 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-682\nComponents:\n - input (input) params={\"shape\":[1,3,44,44]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,44,44]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":54,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":54,\"outChannels\":10,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":10,\"outFeatures\":28}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 213-token sequences with 79 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-683\nComponents:\n - input (input) params={\"shape\":[1,213]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,213]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":15940,\"embeddingDim\":96}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":96,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":96,\"outFeatures\":79}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 224-token sequences with 50 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-684\nComponents:\n - input (input) params={\"shape\":[1,224]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,224]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":26430,\"embeddingDim\":608}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":608,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[608]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":608,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[608]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":608,\"outFeatures\":50}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 1982-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-686\nComponents:\n - input (input) params={\"shape\":[1,44]}\n - fc1 (linear) params={\"inFeatures\":44,\"outFeatures\":1982}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":1982,\"outFeatures\":1982}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":1982,\"outFeatures\":15}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":44,\"outFeatures\":280}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":280,\"outFeatures\":280}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":280,\"outFeatures\":15}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 138-feature, 77-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-687\nComponents:\n - input (input) params={\"shape\":[1,138]}\n - fc1 (linear) params={\"inFeatures\":138,\"outFeatures\":404}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":404,\"outFeatures\":204}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":204,\"outFeatures\":296}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":296,\"outFeatures\":247}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":247,\"outFeatures\":325}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":325,\"outFeatures\":77}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":404}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":204}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":296}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":247}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":325}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 90-feature user input and a 167-feature item input, each through its own 2-layer MLP tower ending at width 479, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-688\nComponents:\n - user_input (input) params={\"shape\":[1,90]}\n - item_input (input) params={\"shape\":[1,167]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,90]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,167]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":90,\"outFeatures\":479}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":479,\"outFeatures\":479}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":167,\"outFeatures\":479}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":479,\"outFeatures\":479}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":958,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (113-feature input, 40 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-689\nComponents:\n - input (input) params={\"shape\":[1,113]}\n - fc1 (linear) params={\"inFeatures\":113,\"outFeatures\":14}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":14,\"outFeatures\":14}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":14,\"outFeatures\":40}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":113,\"outFeatures\":1336}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1336,\"outFeatures\":1336}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1336,\"outFeatures\":40}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 137-feature input with 62 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-690\nComponents:\n - input (input) params={\"shape\":[1,137]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,137]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":137,\"outFeatures\":922}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":922,\"outFeatures\":690}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":690,\"outFeatures\":693}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":693,\"outFeatures\":743}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":743,\"outFeatures\":530}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":530,\"outFeatures\":302}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":302,\"outFeatures\":62}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 876-dim input: encode down to a 185-dim bottleneck and decode back to 876. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-691\nComponents:\n - input (input) params={\"shape\":[1,876]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,876]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":876,\"outFeatures\":827}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":827,\"outFeatures\":185}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":185,\"outFeatures\":827}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":827,\"outFeatures\":876}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x60x60 image with 28 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-692\nComponents:\n - input (input) params={\"shape\":[1,3,60,60]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,60,60]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":20,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":20,\"outChannels\":51,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":51,\"outFeatures\":28}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 391-token sequences with 38 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-693\nComponents:\n - input (input) params={\"shape\":[1,391]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,391]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":27580,\"embeddingDim\":86}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":86,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":86,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":86,\"outFeatures\":38}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 267-token sequences with 13 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-694\nComponents:\n - input (input) params={\"shape\":[1,267]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,267]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":37919,\"embeddingDim\":160}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":160,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[160]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":160,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[160]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":160,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[160]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":160,\"outFeatures\":13}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 3914-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-696\nComponents:\n - input (input) params={\"shape\":[1,100]}\n - fc1 (linear) params={\"inFeatures\":100,\"outFeatures\":3914}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3914,\"outFeatures\":3914}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":3914,\"outFeatures\":49}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":100,\"outFeatures\":321}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":321,\"outFeatures\":321}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":321,\"outFeatures\":49}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 65-feature, 40-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-697\nComponents:\n - input (input) params={\"shape\":[1,65]}\n - fc1 (linear) params={\"inFeatures\":65,\"outFeatures\":484}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":484,\"outFeatures\":432}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":432,\"outFeatures\":236}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":236,\"outFeatures\":271}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":271,\"outFeatures\":257}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":257,\"outFeatures\":40}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":484}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":432}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":236}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":271}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":257}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 195-feature user input and a 141-feature item input, each through its own 2-layer MLP tower ending at width 123, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-698\nComponents:\n - user_input (input) params={\"shape\":[1,195]}\n - item_input (input) params={\"shape\":[1,141]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,195]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,141]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":195,\"outFeatures\":123}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":123,\"outFeatures\":123}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":141,\"outFeatures\":123}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":123,\"outFeatures\":123}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":246,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (96-feature input, 44 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-699\nComponents:\n - input (input) params={\"shape\":[1,96]}\n - fc1 (linear) params={\"inFeatures\":96,\"outFeatures\":17}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":17,\"outFeatures\":17}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":17,\"outFeatures\":44}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":96,\"outFeatures\":764}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":764,\"outFeatures\":764}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":764,\"outFeatures\":44}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 51-feature input with 34 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-700\nComponents:\n - input (input) params={\"shape\":[1,51]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,51]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":51,\"outFeatures\":917}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":917,\"outFeatures\":449}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":449,\"outFeatures\":865}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":865,\"outFeatures\":162}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":162,\"outFeatures\":189}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":189,\"outFeatures\":149}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":149,\"outFeatures\":34}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1779-dim input: encode down to a 211-dim bottleneck and decode back to 1779. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-701\nComponents:\n - input (input) params={\"shape\":[1,1779]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1779]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1779,\"outFeatures\":555}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":555,\"outFeatures\":211}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":211,\"outFeatures\":555}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":555,\"outFeatures\":1779}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x42x42 image with 90 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-702\nComponents:\n - input (input) params={\"shape\":[1,3,42,42]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,42,42]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":62,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":62,\"outChannels\":25,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":25,\"outChannels\":10,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":10,\"outFeatures\":90}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 356-token sequences with 32 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-703\nComponents:\n - input (input) params={\"shape\":[1,356]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,356]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":39880,\"embeddingDim\":236}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":236,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":236,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":236,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":236,\"outFeatures\":32}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 139-token sequences with 65 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-704\nComponents:\n - input (input) params={\"shape\":[1,139]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,139]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":34650,\"embeddingDim\":688}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":688,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[688]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":688,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[688]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":688,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[688]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":688,\"outFeatures\":65}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 2367-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-706\nComponents:\n - input (input) params={\"shape\":[1,183]}\n - fc1 (linear) params={\"inFeatures\":183,\"outFeatures\":2367}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2367,\"outFeatures\":2367}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2367,\"outFeatures\":2367}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":2367,\"outFeatures\":38}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":183,\"outFeatures\":203}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":203,\"outFeatures\":203}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":203,\"outFeatures\":203}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":203,\"outFeatures\":38}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 33-feature, 38-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-707\nComponents:\n - input (input) params={\"shape\":[1,33]}\n - fc1 (linear) params={\"inFeatures\":33,\"outFeatures\":310}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":310,\"outFeatures\":153}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":153,\"outFeatures\":201}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":201,\"outFeatures\":370}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":370,\"outFeatures\":218}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":218,\"outFeatures\":38}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":310}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":153}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":201}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":370}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":218}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 239-feature user input and a 51-feature item input, each through its own 2-layer MLP tower ending at width 51, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-708\nComponents:\n - user_input (input) params={\"shape\":[1,239]}\n - item_input (input) params={\"shape\":[1,51]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,239]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,51]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":239,\"outFeatures\":51}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":51,\"outFeatures\":51}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":51,\"outFeatures\":51}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":51,\"outFeatures\":51}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":102,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (70-feature input, 44 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-709\nComponents:\n - input (input) params={\"shape\":[1,70]}\n - fc1 (linear) params={\"inFeatures\":70,\"outFeatures\":19}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":19,\"outFeatures\":19}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":19,\"outFeatures\":44}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":70,\"outFeatures\":721}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":721,\"outFeatures\":721}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":721,\"outFeatures\":44}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 184-feature input with 122 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-710\nComponents:\n - input (input) params={\"shape\":[1,184]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,184]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":184,\"outFeatures\":452}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":452,\"outFeatures\":168}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":168,\"outFeatures\":647}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":647,\"outFeatures\":122}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 115-dim input: encode down to a 139-dim bottleneck and decode back to 115. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-711\nComponents:\n - input (input) params={\"shape\":[1,115]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,115]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":115,\"outFeatures\":579}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":579,\"outFeatures\":139}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":139,\"outFeatures\":579}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":579,\"outFeatures\":115}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x27x27 image with 31 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-712\nComponents:\n - input (input) params={\"shape\":[1,3,27,27]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,27,27]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":29,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":29,\"outChannels\":34,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":34,\"outChannels\":37,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":37,\"outFeatures\":31}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 65-token sequences with 26 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-713\nComponents:\n - input (input) params={\"shape\":[1,65]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,65]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":38065,\"embeddingDim\":110}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":110,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":110,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":110,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":110,\"outFeatures\":26}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 205-token sequences with 59 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-714\nComponents:\n - input (input) params={\"shape\":[1,205]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,205]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":28075,\"embeddingDim\":176}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":176,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[176]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":176,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[176]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":176,\"outFeatures\":59}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 1637-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-716\nComponents:\n - input (input) params={\"shape\":[1,44]}\n - fc1 (linear) params={\"inFeatures\":44,\"outFeatures\":1637}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":1637,\"outFeatures\":1637}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":1637,\"outFeatures\":5}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":44,\"outFeatures\":69}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":69,\"outFeatures\":69}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":69,\"outFeatures\":5}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 198-feature, 60-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-717\nComponents:\n - input (input) params={\"shape\":[1,198]}\n - fc1 (linear) params={\"inFeatures\":198,\"outFeatures\":436}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":436,\"outFeatures\":56}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":56,\"outFeatures\":461}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":461,\"outFeatures\":293}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":293,\"outFeatures\":62}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":62,\"outFeatures\":60}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":436}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":56}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":461}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":293}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":62}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 92-feature user input and a 54-feature item input, each through its own 2-layer MLP tower ending at width 295, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-718\nComponents:\n - user_input (input) params={\"shape\":[1,92]}\n - item_input (input) params={\"shape\":[1,54]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,92]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,54]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":92,\"outFeatures\":295}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":295,\"outFeatures\":295}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":54,\"outFeatures\":295}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":295,\"outFeatures\":295}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":590,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (80-feature input, 47 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-719\nComponents:\n - input (input) params={\"shape\":[1,80]}\n - fc1 (linear) params={\"inFeatures\":80,\"outFeatures\":20}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":20,\"outFeatures\":20}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":20,\"outFeatures\":47}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":80,\"outFeatures\":833}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":833,\"outFeatures\":833}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":833,\"outFeatures\":47}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 462-feature input with 128 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-720\nComponents:\n - input (input) params={\"shape\":[1,462]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,462]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":462,\"outFeatures\":422}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":422,\"outFeatures\":1019}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":1019,\"outFeatures\":65}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":65,\"outFeatures\":433}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":433,\"outFeatures\":128}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 135-dim input: encode down to a 247-dim bottleneck and decode back to 135. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-721\nComponents:\n - input (input) params={\"shape\":[1,135]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,135]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":135,\"outFeatures\":203}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":203,\"outFeatures\":247}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":247,\"outFeatures\":203}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":203,\"outFeatures\":135}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x36x36 image with 52 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-722\nComponents:\n - input (input) params={\"shape\":[1,3,36,36]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,36,36]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":36,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":36,\"outChannels\":26,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":26,\"outChannels\":39,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":39,\"outChannels\":52,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":52,\"outFeatures\":52}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 383-token sequences with 45 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-723\nComponents:\n - input (input) params={\"shape\":[1,383]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,383]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":34253,\"embeddingDim\":28}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":28,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":28,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":28,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":28,\"outFeatures\":45}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 113-token sequences with 53 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-724\nComponents:\n - input (input) params={\"shape\":[1,113]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,113]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":31331,\"embeddingDim\":560}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":560,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[560]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":560,\"outFeatures\":53}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3971-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-726\nComponents:\n - input (input) params={\"shape\":[1,42]}\n - fc1 (linear) params={\"inFeatures\":42,\"outFeatures\":3971}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3971,\"outFeatures\":3971}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3971,\"outFeatures\":3971}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3971,\"outFeatures\":3971}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3971,\"outFeatures\":8}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":42,\"outFeatures\":139}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":139,\"outFeatures\":139}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":139,\"outFeatures\":139}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":139,\"outFeatures\":139}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":139,\"outFeatures\":8}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 145-feature, 29-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-727\nComponents:\n - input (input) params={\"shape\":[1,145]}\n - fc1 (linear) params={\"inFeatures\":145,\"outFeatures\":102}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":102,\"outFeatures\":286}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":286,\"outFeatures\":29}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":102}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":286}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 132-feature user input and a 84-feature item input, each through its own 2-layer MLP tower ending at width 481, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-728\nComponents:\n - user_input (input) params={\"shape\":[1,132]}\n - item_input (input) params={\"shape\":[1,84]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,132]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,84]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":132,\"outFeatures\":481}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":481,\"outFeatures\":481}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":84,\"outFeatures\":481}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":481,\"outFeatures\":481}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":962,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (98-feature input, 20 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-729\nComponents:\n - input (input) params={\"shape\":[1,98]}\n - fc1 (linear) params={\"inFeatures\":98,\"outFeatures\":11}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":11,\"outFeatures\":11}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":11,\"outFeatures\":20}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":98,\"outFeatures\":863}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":863,\"outFeatures\":863}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":863,\"outFeatures\":20}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 154-feature input with 75 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-730\nComponents:\n - input (input) params={\"shape\":[1,154]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,154]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":154,\"outFeatures\":569}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":569,\"outFeatures\":173}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":173,\"outFeatures\":54}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":54,\"outFeatures\":490}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":490,\"outFeatures\":213}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":213,\"outFeatures\":75}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 144-dim input: encode down to a 79-dim bottleneck and decode back to 144. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-731\nComponents:\n - input (input) params={\"shape\":[1,144]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,144]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":144,\"outFeatures\":551}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":551,\"outFeatures\":79}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":79,\"outFeatures\":551}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":551,\"outFeatures\":144}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x63x63 image with 59 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-732\nComponents:\n - input (input) params={\"shape\":[1,3,63,63]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,63,63]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":29,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":29,\"outChannels\":23,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":23,\"outChannels\":12,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":12,\"outChannels\":52,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":52,\"outFeatures\":59}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 114-token sequences with 24 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-733\nComponents:\n - input (input) params={\"shape\":[1,114]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,114]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":31255,\"embeddingDim\":48}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":48,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":48,\"outFeatures\":24}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 229-token sequences with 72 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-734\nComponents:\n - input (input) params={\"shape\":[1,229]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,229]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":35494,\"embeddingDim\":448}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":448,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[448]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":448,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[448]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":448,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[448]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":448,\"outFeatures\":72}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 1683-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-736\nComponents:\n - input (input) params={\"shape\":[1,56]}\n - fc1 (linear) params={\"inFeatures\":56,\"outFeatures\":1683}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":1683,\"outFeatures\":1683}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":1683,\"outFeatures\":1683}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":1683,\"outFeatures\":36}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":56,\"outFeatures\":151}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":151,\"outFeatures\":151}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":151,\"outFeatures\":151}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":151,\"outFeatures\":36}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 108-feature, 52-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-737\nComponents:\n - input (input) params={\"shape\":[1,108]}\n - fc1 (linear) params={\"inFeatures\":108,\"outFeatures\":126}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":126,\"outFeatures\":327}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":327,\"outFeatures\":277}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":277,\"outFeatures\":144}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":144,\"outFeatures\":510}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":510,\"outFeatures\":52}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":126}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":327}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":277}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":144}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":510}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 112-feature user input and a 205-feature item input, each through its own 2-layer MLP tower ending at width 151, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-738\nComponents:\n - user_input (input) params={\"shape\":[1,112]}\n - item_input (input) params={\"shape\":[1,205]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,112]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,205]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":112,\"outFeatures\":151}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":151,\"outFeatures\":151}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":205,\"outFeatures\":151}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":151,\"outFeatures\":151}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":302,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (29-feature input, 11 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-739\nComponents:\n - input (input) params={\"shape\":[1,29]}\n - fc1 (linear) params={\"inFeatures\":29,\"outFeatures\":7}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":7,\"outFeatures\":7}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":7,\"outFeatures\":11}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":29,\"outFeatures\":909}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":909,\"outFeatures\":909}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":909,\"outFeatures\":11}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 393-feature input with 81 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-740\nComponents:\n - input (input) params={\"shape\":[1,393]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,393]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":393,\"outFeatures\":744}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":744,\"outFeatures\":979}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":979,\"outFeatures\":933}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":933,\"outFeatures\":81}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1947-dim input: encode down to a 176-dim bottleneck and decode back to 1947. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-741\nComponents:\n - input (input) params={\"shape\":[1,1947]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1947]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1947,\"outFeatures\":740}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":740,\"outFeatures\":176}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":176,\"outFeatures\":740}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":740,\"outFeatures\":1947}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x38x38 image with 88 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-742\nComponents:\n - input (input) params={\"shape\":[1,3,38,38]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,38,38]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":49,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":49,\"outChannels\":23,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":23,\"outFeatures\":88}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 429-token sequences with 45 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-743\nComponents:\n - input (input) params={\"shape\":[1,429]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,429]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":36746,\"embeddingDim\":72}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":72,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":72,\"outFeatures\":45}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 229-token sequences with 91 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-744\nComponents:\n - input (input) params={\"shape\":[1,229]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,229]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":29611,\"embeddingDim\":464}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":464,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[464]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":464,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[464]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":464,\"outFeatures\":91}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 3439-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-746\nComponents:\n - input (input) params={\"shape\":[1,253]}\n - fc1 (linear) params={\"inFeatures\":253,\"outFeatures\":3439}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3439,\"outFeatures\":3439}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3439,\"outFeatures\":3439}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":3439,\"outFeatures\":21}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":253,\"outFeatures\":164}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":164,\"outFeatures\":164}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":164,\"outFeatures\":164}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":164,\"outFeatures\":21}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 199-feature, 56-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-747\nComponents:\n - input (input) params={\"shape\":[1,199]}\n - fc1 (linear) params={\"inFeatures\":199,\"outFeatures\":498}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":498,\"outFeatures\":369}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":369,\"outFeatures\":364}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":364,\"outFeatures\":406}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":406,\"outFeatures\":56}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":498}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":369}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":364}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":406}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 200-feature user input and a 107-feature item input, each through its own 2-layer MLP tower ending at width 66, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-748\nComponents:\n - user_input (input) params={\"shape\":[1,200]}\n - item_input (input) params={\"shape\":[1,107]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,200]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,107]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":200,\"outFeatures\":66}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":66,\"outFeatures\":66}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":107,\"outFeatures\":66}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":66,\"outFeatures\":66}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":132,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (75-feature input, 42 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-749\nComponents:\n - input (input) params={\"shape\":[1,75]}\n - fc1 (linear) params={\"inFeatures\":75,\"outFeatures\":12}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":12,\"outFeatures\":12}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":12,\"outFeatures\":42}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":75,\"outFeatures\":971}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":971,\"outFeatures\":971}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":971,\"outFeatures\":42}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 34-feature input with 137 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-750\nComponents:\n - input (input) params={\"shape\":[1,34]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,34]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":34,\"outFeatures\":649}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":649,\"outFeatures\":610}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":610,\"outFeatures\":961}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":961,\"outFeatures\":137}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 173-dim input: encode down to a 184-dim bottleneck and decode back to 173. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-751\nComponents:\n - input (input) params={\"shape\":[1,173]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,173]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":173,\"outFeatures\":751}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":751,\"outFeatures\":184}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":184,\"outFeatures\":751}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":751,\"outFeatures\":173}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x58x58 image with 38 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-752\nComponents:\n - input (input) params={\"shape\":[1,3,58,58]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,58,58]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":52,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":52,\"outChannels\":61,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":61,\"outFeatures\":38}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 174-token sequences with 87 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-753\nComponents:\n - input (input) params={\"shape\":[1,174]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,174]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":19312,\"embeddingDim\":236}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":236,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":236,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":236,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":236,\"outFeatures\":87}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 346-token sequences with 10 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-754\nComponents:\n - input (input) params={\"shape\":[1,346]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,346]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":39395,\"embeddingDim\":40}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":40,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[40]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":40,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[40]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":40,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[40]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":40,\"outFeatures\":10}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (98) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-755\nComponents:\n - input (input) params={\"shape\":[1,105]}\n - embed (embedding) params={\"numEmbeddings\":18544,\"embeddingDim\":98}\n - attn (multiHeadAttention) params={\"embedDim\":98,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":98,\"outFeatures\":64}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 1578-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-756\nComponents:\n - input (input) params={\"shape\":[1,126]}\n - fc1 (linear) params={\"inFeatures\":126,\"outFeatures\":1578}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":1578,\"outFeatures\":1578}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":1578,\"outFeatures\":1578}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":1578,\"outFeatures\":1578}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":1578,\"outFeatures\":18}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":126,\"outFeatures\":357}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":357,\"outFeatures\":357}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":357,\"outFeatures\":357}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":357,\"outFeatures\":357}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":357,\"outFeatures\":18}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 161-feature, 42-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-757\nComponents:\n - input (input) params={\"shape\":[1,161]}\n - fc1 (linear) params={\"inFeatures\":161,\"outFeatures\":182}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":182,\"outFeatures\":93}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":93,\"outFeatures\":42}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":182}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":93}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 233-feature user input and a 143-feature item input, each through its own 2-layer MLP tower ending at width 112, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-758\nComponents:\n - user_input (input) params={\"shape\":[1,233]}\n - item_input (input) params={\"shape\":[1,143]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,233]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,143]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":233,\"outFeatures\":112}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":112,\"outFeatures\":112}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":143,\"outFeatures\":112}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":112,\"outFeatures\":112}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":224,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (103-feature input, 42 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-759\nComponents:\n - input (input) params={\"shape\":[1,103]}\n - fc1 (linear) params={\"inFeatures\":103,\"outFeatures\":14}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":14,\"outFeatures\":14}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":14,\"outFeatures\":42}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":103,\"outFeatures\":1259}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1259,\"outFeatures\":1259}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1259,\"outFeatures\":42}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 423-feature input with 91 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-760\nComponents:\n - input (input) params={\"shape\":[1,423]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,423]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":423,\"outFeatures\":923}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":923,\"outFeatures\":636}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":636,\"outFeatures\":91}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1384-dim input: encode down to a 234-dim bottleneck and decode back to 1384. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-761\nComponents:\n - input (input) params={\"shape\":[1,1384]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1384]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1384,\"outFeatures\":203}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":203,\"outFeatures\":234}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":234,\"outFeatures\":203}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":203,\"outFeatures\":1384}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x56x56 image with 5 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-762\nComponents:\n - input (input) params={\"shape\":[1,3,56,56]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,56,56]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":20,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":20,\"outChannels\":34,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":34,\"outChannels\":33,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":33,\"outChannels\":12,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":12,\"outFeatures\":5}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 424-token sequences with 34 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-763\nComponents:\n - input (input) params={\"shape\":[1,424]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,424]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":47047,\"embeddingDim\":88}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":88,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":88,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":88,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":88,\"outFeatures\":34}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 348-token sequences with 81 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-764\nComponents:\n - input (input) params={\"shape\":[1,348]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,348]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":47418,\"embeddingDim\":76}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":76,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[76]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":76,\"outFeatures\":81}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (226) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-765\nComponents:\n - input (input) params={\"shape\":[1,229]}\n - embed (embedding) params={\"numEmbeddings\":33802,\"embeddingDim\":226}\n - attn (multiHeadAttention) params={\"embedDim\":226,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":226,\"outFeatures\":69}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 2018-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-766\nComponents:\n - input (input) params={\"shape\":[1,141]}\n - fc1 (linear) params={\"inFeatures\":141,\"outFeatures\":2018}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2018,\"outFeatures\":2018}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":2018,\"outFeatures\":21}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":141,\"outFeatures\":194}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":194,\"outFeatures\":194}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":194,\"outFeatures\":21}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 142-feature, 2-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-767\nComponents:\n - input (input) params={\"shape\":[1,142]}\n - fc1 (linear) params={\"inFeatures\":142,\"outFeatures\":448}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":448,\"outFeatures\":76}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":76,\"outFeatures\":438}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":438,\"outFeatures\":2}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":448}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":76}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":438}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 243-feature user input and a 175-feature item input, each through its own 2-layer MLP tower ending at width 288, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-768\nComponents:\n - user_input (input) params={\"shape\":[1,243]}\n - item_input (input) params={\"shape\":[1,175]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,243]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,175]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":243,\"outFeatures\":288}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":288,\"outFeatures\":288}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":175,\"outFeatures\":288}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":288,\"outFeatures\":288}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":576,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (58-feature input, 45 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-769\nComponents:\n - input (input) params={\"shape\":[1,58]}\n - fc1 (linear) params={\"inFeatures\":58,\"outFeatures\":18}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":18,\"outFeatures\":18}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":18,\"outFeatures\":45}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":58,\"outFeatures\":1333}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1333,\"outFeatures\":1333}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1333,\"outFeatures\":45}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 202-feature input with 72 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-770\nComponents:\n - input (input) params={\"shape\":[1,202]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,202]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":202,\"outFeatures\":640}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":640,\"outFeatures\":610}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":610,\"outFeatures\":751}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":751,\"outFeatures\":72}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 343-dim input: encode down to a 240-dim bottleneck and decode back to 343. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-771\nComponents:\n - input (input) params={\"shape\":[1,343]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,343]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":343,\"outFeatures\":381}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":381,\"outFeatures\":240}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":240,\"outFeatures\":381}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":381,\"outFeatures\":343}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x38x38 image with 80 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-772\nComponents:\n - input (input) params={\"shape\":[1,3,38,38]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,38,38]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":35,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":35,\"outChannels\":49,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":49,\"outChannels\":28,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":28,\"outFeatures\":80}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 437-token sequences with 11 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-773\nComponents:\n - input (input) params={\"shape\":[1,437]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,437]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":30809,\"embeddingDim\":176}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":176,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":176,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":176,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":176,\"outFeatures\":11}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 423-token sequences with 76 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-774\nComponents:\n - input (input) params={\"shape\":[1,423]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,423]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":47121,\"embeddingDim\":40}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":40,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[40]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":40,\"outFeatures\":76}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (268) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-775\nComponents:\n - input (input) params={\"shape\":[1,238]}\n - embed (embedding) params={\"numEmbeddings\":15965,\"embeddingDim\":268}\n - attn (multiHeadAttention) params={\"embedDim\":268,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":268,\"outFeatures\":22}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":4}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 2817-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-776\nComponents:\n - input (input) params={\"shape\":[1,214]}\n - fc1 (linear) params={\"inFeatures\":214,\"outFeatures\":2817}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2817,\"outFeatures\":2817}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":2817,\"outFeatures\":39}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":214,\"outFeatures\":66}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":66,\"outFeatures\":66}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":66,\"outFeatures\":39}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 256-feature, 12-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-777\nComponents:\n - input (input) params={\"shape\":[1,256]}\n - fc1 (linear) params={\"inFeatures\":256,\"outFeatures\":62}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":62,\"outFeatures\":343}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":343,\"outFeatures\":12}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":62}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":343}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 231-feature user input and a 177-feature item input, each through its own 2-layer MLP tower ending at width 375, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-778\nComponents:\n - user_input (input) params={\"shape\":[1,231]}\n - item_input (input) params={\"shape\":[1,177]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,231]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,177]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":231,\"outFeatures\":375}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":375,\"outFeatures\":375}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":177,\"outFeatures\":375}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":375,\"outFeatures\":375}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":750,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (36-feature input, 25 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-779\nComponents:\n - input (input) params={\"shape\":[1,36]}\n - fc1 (linear) params={\"inFeatures\":36,\"outFeatures\":8}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":8,\"outFeatures\":8}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":8,\"outFeatures\":25}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":36,\"outFeatures\":1373}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1373,\"outFeatures\":1373}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1373,\"outFeatures\":25}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 186-feature input with 146 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-780\nComponents:\n - input (input) params={\"shape\":[1,186]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,186]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":186,\"outFeatures\":981}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":981,\"outFeatures\":297}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":297,\"outFeatures\":146}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 672-dim input: encode down to a 44-dim bottleneck and decode back to 672. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-781\nComponents:\n - input (input) params={\"shape\":[1,672]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,672]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":672,\"outFeatures\":847}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":847,\"outFeatures\":44}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":44,\"outFeatures\":847}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":847,\"outFeatures\":672}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x56x56 image with 15 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-782\nComponents:\n - input (input) params={\"shape\":[1,3,56,56]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,56,56]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":49,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":49,\"outChannels\":23,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":23,\"outFeatures\":15}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 87-token sequences with 69 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-783\nComponents:\n - input (input) params={\"shape\":[1,87]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,87]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":9816,\"embeddingDim\":244}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":244,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":244,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":244,\"outFeatures\":69}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 251-token sequences with 48 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-784\nComponents:\n - input (input) params={\"shape\":[1,251]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,251]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":35959,\"embeddingDim\":312}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":312,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[312]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":312,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[312]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":312,\"outFeatures\":48}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 3012-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-786\nComponents:\n - input (input) params={\"shape\":[1,230]}\n - fc1 (linear) params={\"inFeatures\":230,\"outFeatures\":3012}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3012,\"outFeatures\":3012}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3012,\"outFeatures\":3012}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":3012,\"outFeatures\":7}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":230,\"outFeatures\":76}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":76,\"outFeatures\":76}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":76,\"outFeatures\":76}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":76,\"outFeatures\":7}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 114-feature, 80-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-787\nComponents:\n - input (input) params={\"shape\":[1,114]}\n - fc1 (linear) params={\"inFeatures\":114,\"outFeatures\":50}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":50,\"outFeatures\":424}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":424,\"outFeatures\":231}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":231,\"outFeatures\":383}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":383,\"outFeatures\":80}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":50}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":424}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":231}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":383}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 255-feature user input and a 186-feature item input, each through its own 2-layer MLP tower ending at width 212, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-788\nComponents:\n - user_input (input) params={\"shape\":[1,255]}\n - item_input (input) params={\"shape\":[1,186]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,255]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,186]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":255,\"outFeatures\":212}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":212,\"outFeatures\":212}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":186,\"outFeatures\":212}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":212,\"outFeatures\":212}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":424,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (48-feature input, 7 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-789\nComponents:\n - input (input) params={\"shape\":[1,48]}\n - fc1 (linear) params={\"inFeatures\":48,\"outFeatures\":22}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":22,\"outFeatures\":22}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":22,\"outFeatures\":7}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":48,\"outFeatures\":687}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":687,\"outFeatures\":687}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":687,\"outFeatures\":7}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 55-feature input with 42 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-790\nComponents:\n - input (input) params={\"shape\":[1,55]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,55]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":55,\"outFeatures\":634}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":634,\"outFeatures\":967}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":967,\"outFeatures\":982}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":982,\"outFeatures\":437}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":437,\"outFeatures\":663}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":663,\"outFeatures\":513}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":513,\"outFeatures\":42}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 238-dim input: encode down to a 90-dim bottleneck and decode back to 238. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-791\nComponents:\n - input (input) params={\"shape\":[1,238]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,238]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":238,\"outFeatures\":953}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":953,\"outFeatures\":90}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":90,\"outFeatures\":953}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":953,\"outFeatures\":238}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x61x61 image with 54 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-792\nComponents:\n - input (input) params={\"shape\":[1,3,61,61]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,61,61]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":37,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":37,\"outChannels\":53,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":53,\"outChannels\":61,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":61,\"outFeatures\":54}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 123-token sequences with 72 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-793\nComponents:\n - input (input) params={\"shape\":[1,123]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,123]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":15754,\"embeddingDim\":64}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":64,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":64,\"outFeatures\":72}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 400-token sequences with 3 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-794\nComponents:\n - input (input) params={\"shape\":[1,400]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,400]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":43355,\"embeddingDim\":640}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":640,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[640]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":640,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[640]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":640,\"outFeatures\":3}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (414) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-795\nComponents:\n - input (input) params={\"shape\":[1,316]}\n - embed (embedding) params={\"numEmbeddings\":48413,\"embeddingDim\":414}\n - attn (multiHeadAttention) params={\"embedDim\":414,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":414,\"outFeatures\":14}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 4048-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-796\nComponents:\n - input (input) params={\"shape\":[1,170]}\n - fc1 (linear) params={\"inFeatures\":170,\"outFeatures\":4048}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":4048,\"outFeatures\":4048}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":4048,\"outFeatures\":25}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":170,\"outFeatures\":130}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":130,\"outFeatures\":130}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":130,\"outFeatures\":25}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 241-feature, 48-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-797\nComponents:\n - input (input) params={\"shape\":[1,241]}\n - fc1 (linear) params={\"inFeatures\":241,\"outFeatures\":458}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":458,\"outFeatures\":168}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":168,\"outFeatures\":426}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":426,\"outFeatures\":398}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":398,\"outFeatures\":48}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":458}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":168}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":426}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":398}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 148-feature user input and a 202-feature item input, each through its own 2-layer MLP tower ending at width 208, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-798\nComponents:\n - user_input (input) params={\"shape\":[1,148]}\n - item_input (input) params={\"shape\":[1,202]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,148]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,202]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":148,\"outFeatures\":208}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":208,\"outFeatures\":208}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":202,\"outFeatures\":208}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":208,\"outFeatures\":208}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":416,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (46-feature input, 4 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-799\nComponents:\n - input (input) params={\"shape\":[1,46]}\n - fc1 (linear) params={\"inFeatures\":46,\"outFeatures\":5}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":5,\"outFeatures\":5}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":5,\"outFeatures\":4}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":46,\"outFeatures\":1000}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1000,\"outFeatures\":1000}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1000,\"outFeatures\":4}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 22-feature input with 189 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-800\nComponents:\n - input (input) params={\"shape\":[1,22]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,22]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":22,\"outFeatures\":313}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":313,\"outFeatures\":939}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":939,\"outFeatures\":189}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1162-dim input: encode down to a 224-dim bottleneck and decode back to 1162. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-801\nComponents:\n - input (input) params={\"shape\":[1,1162]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1162]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1162,\"outFeatures\":592}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":592,\"outFeatures\":224}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":224,\"outFeatures\":592}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":592,\"outFeatures\":1162}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x24x24 image with 9 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-802\nComponents:\n - input (input) params={\"shape\":[1,3,24,24]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,24,24]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":56,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":56,\"outChannels\":48,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":48,\"outChannels\":55,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":55,\"outFeatures\":9}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 296-token sequences with 4 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-803\nComponents:\n - input (input) params={\"shape\":[1,296]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,296]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":44039,\"embeddingDim\":432}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":432,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":432,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":432,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":432,\"outFeatures\":4}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 173-token sequences with 85 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-804\nComponents:\n - input (input) params={\"shape\":[1,173]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,173]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":43266,\"embeddingDim\":100}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":100,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[100]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":100,\"outFeatures\":85}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (298) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-805\nComponents:\n - input (input) params={\"shape\":[1,48]}\n - embed (embedding) params={\"numEmbeddings\":28752,\"embeddingDim\":298}\n - attn (multiHeadAttention) params={\"embedDim\":298,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":298,\"outFeatures\":22}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 2595-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-806\nComponents:\n - input (input) params={\"shape\":[1,53]}\n - fc1 (linear) params={\"inFeatures\":53,\"outFeatures\":2595}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2595,\"outFeatures\":2595}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2595,\"outFeatures\":2595}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":2595,\"outFeatures\":2595}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":2595,\"outFeatures\":47}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":53,\"outFeatures\":220}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":220,\"outFeatures\":220}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":220,\"outFeatures\":220}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":220,\"outFeatures\":220}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":220,\"outFeatures\":47}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 143-feature, 32-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-807\nComponents:\n - input (input) params={\"shape\":[1,143]}\n - fc1 (linear) params={\"inFeatures\":143,\"outFeatures\":426}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":426,\"outFeatures\":109}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":109,\"outFeatures\":94}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":94,\"outFeatures\":168}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":168,\"outFeatures\":380}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":380,\"outFeatures\":32}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":426}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":109}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":94}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":168}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":380}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 200-feature user input and a 79-feature item input, each through its own 2-layer MLP tower ending at width 254, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-808\nComponents:\n - user_input (input) params={\"shape\":[1,200]}\n - item_input (input) params={\"shape\":[1,79]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,200]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,79]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":200,\"outFeatures\":254}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":254,\"outFeatures\":254}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":79,\"outFeatures\":254}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":254,\"outFeatures\":254}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":508,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (42-feature input, 41 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-809\nComponents:\n - input (input) params={\"shape\":[1,42]}\n - fc1 (linear) params={\"inFeatures\":42,\"outFeatures\":14}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":14,\"outFeatures\":14}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":14,\"outFeatures\":41}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":42,\"outFeatures\":753}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":753,\"outFeatures\":753}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":753,\"outFeatures\":41}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 458-feature input with 79 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-810\nComponents:\n - input (input) params={\"shape\":[1,458]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,458]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":458,\"outFeatures\":780}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":780,\"outFeatures\":233}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":233,\"outFeatures\":79}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1847-dim input: encode down to a 16-dim bottleneck and decode back to 1847. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-811\nComponents:\n - input (input) params={\"shape\":[1,1847]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1847]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1847,\"outFeatures\":171}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":171,\"outFeatures\":16}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":16,\"outFeatures\":171}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":171,\"outFeatures\":1847}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x34x34 image with 96 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-812\nComponents:\n - input (input) params={\"shape\":[1,3,34,34]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,34,34]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":9,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":9,\"outChannels\":60,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":60,\"outChannels\":43,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":43,\"outChannels\":30,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":30,\"outFeatures\":96}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 138-token sequences with 69 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-813\nComponents:\n - input (input) params={\"shape\":[1,138]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,138]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":35028,\"embeddingDim\":272}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":272,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":272,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":272,\"outFeatures\":69}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 197-token sequences with 84 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-814\nComponents:\n - input (input) params={\"shape\":[1,197]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,197]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":19705,\"embeddingDim\":64}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":64,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[64]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":64,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[64]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":64,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[64]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":64,\"outFeatures\":84}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 2760-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-816\nComponents:\n - input (input) params={\"shape\":[1,176]}\n - fc1 (linear) params={\"inFeatures\":176,\"outFeatures\":2760}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2760,\"outFeatures\":2760}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2760,\"outFeatures\":2760}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":2760,\"outFeatures\":2760}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":2760,\"outFeatures\":23}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":176,\"outFeatures\":210}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":210,\"outFeatures\":210}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":210,\"outFeatures\":210}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":210,\"outFeatures\":210}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":210,\"outFeatures\":23}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 185-feature, 80-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-817\nComponents:\n - input (input) params={\"shape\":[1,185]}\n - fc1 (linear) params={\"inFeatures\":185,\"outFeatures\":111}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":111,\"outFeatures\":268}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":268,\"outFeatures\":213}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":213,\"outFeatures\":54}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":54,\"outFeatures\":404}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":404,\"outFeatures\":80}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":111}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":268}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":213}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":54}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":404}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 160-feature user input and a 123-feature item input, each through its own 2-layer MLP tower ending at width 177, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-818\nComponents:\n - user_input (input) params={\"shape\":[1,160]}\n - item_input (input) params={\"shape\":[1,123]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,160]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,123]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":160,\"outFeatures\":177}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":177,\"outFeatures\":177}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":123,\"outFeatures\":177}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":177,\"outFeatures\":177}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":354,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (83-feature input, 35 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-819\nComponents:\n - input (input) params={\"shape\":[1,83]}\n - fc1 (linear) params={\"inFeatures\":83,\"outFeatures\":5}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":5,\"outFeatures\":5}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":5,\"outFeatures\":35}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":83,\"outFeatures\":1332}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1332,\"outFeatures\":1332}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1332,\"outFeatures\":35}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 186-feature input with 179 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-820\nComponents:\n - input (input) params={\"shape\":[1,186]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,186]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":186,\"outFeatures\":933}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":933,\"outFeatures\":755}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":755,\"outFeatures\":846}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":846,\"outFeatures\":788}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":788,\"outFeatures\":179}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 224-dim input: encode down to a 168-dim bottleneck and decode back to 224. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-821\nComponents:\n - input (input) params={\"shape\":[1,224]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,224]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":224,\"outFeatures\":482}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":482,\"outFeatures\":168}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":168,\"outFeatures\":482}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":482,\"outFeatures\":224}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x55x55 image with 94 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-822\nComponents:\n - input (input) params={\"shape\":[1,3,55,55]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,55,55]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":26,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":26,\"outChannels\":24,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":24,\"outChannels\":16,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":16,\"outFeatures\":94}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 128-token sequences with 10 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-823\nComponents:\n - input (input) params={\"shape\":[1,128]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,128]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":16650,\"embeddingDim\":78}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":78,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":78,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":78,\"outFeatures\":10}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 442-token sequences with 13 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-824\nComponents:\n - input (input) params={\"shape\":[1,442]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,442]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":44650,\"embeddingDim\":288}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":288,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[288]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":288,\"outFeatures\":13}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (460) is not divisible by numHeads (7). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-825\nComponents:\n - input (input) params={\"shape\":[1,508]}\n - embed (embedding) params={\"numEmbeddings\":21848,\"embeddingDim\":460}\n - attn (multiHeadAttention) params={\"embedDim\":460,\"numHeads\":7}\n - head (linear) params={\"inFeatures\":460,\"outFeatures\":46}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":4}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3551-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-826\nComponents:\n - input (input) params={\"shape\":[1,153]}\n - fc1 (linear) params={\"inFeatures\":153,\"outFeatures\":3551}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3551,\"outFeatures\":3551}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3551,\"outFeatures\":3551}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3551,\"outFeatures\":3551}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3551,\"outFeatures\":26}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":153,\"outFeatures\":79}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":79,\"outFeatures\":79}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":79,\"outFeatures\":79}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":79,\"outFeatures\":79}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":79,\"outFeatures\":26}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 74-feature, 77-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-827\nComponents:\n - input (input) params={\"shape\":[1,74]}\n - fc1 (linear) params={\"inFeatures\":74,\"outFeatures\":220}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":220,\"outFeatures\":149}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":149,\"outFeatures\":487}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":487,\"outFeatures\":77}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":220}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":149}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":487}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 90-feature user input and a 103-feature item input, each through its own 2-layer MLP tower ending at width 51, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-828\nComponents:\n - user_input (input) params={\"shape\":[1,90]}\n - item_input (input) params={\"shape\":[1,103]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,90]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,103]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":90,\"outFeatures\":51}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":51,\"outFeatures\":51}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":103,\"outFeatures\":51}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":51,\"outFeatures\":51}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":102,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (34-feature input, 23 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-829\nComponents:\n - input (input) params={\"shape\":[1,34]}\n - fc1 (linear) params={\"inFeatures\":34,\"outFeatures\":15}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":15,\"outFeatures\":15}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":15,\"outFeatures\":23}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":34,\"outFeatures\":814}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":814,\"outFeatures\":814}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":814,\"outFeatures\":23}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 40-feature input with 123 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-830\nComponents:\n - input (input) params={\"shape\":[1,40]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,40]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":40,\"outFeatures\":180}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":180,\"outFeatures\":952}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":952,\"outFeatures\":134}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":134,\"outFeatures\":280}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":280,\"outFeatures\":264}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":264,\"outFeatures\":123}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1260-dim input: encode down to a 41-dim bottleneck and decode back to 1260. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-831\nComponents:\n - input (input) params={\"shape\":[1,1260]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1260]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1260,\"outFeatures\":527}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":527,\"outFeatures\":41}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":41,\"outFeatures\":527}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":527,\"outFeatures\":1260}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x60x60 image with 36 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-832\nComponents:\n - input (input) params={\"shape\":[1,3,60,60]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,60,60]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":40,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":40,\"outChannels\":59,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":59,\"outChannels\":50,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":50,\"outFeatures\":36}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 397-token sequences with 69 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-833\nComponents:\n - input (input) params={\"shape\":[1,397]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,397]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":39433,\"embeddingDim\":512}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":512,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":512,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":512,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":512,\"outFeatures\":69}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 209-token sequences with 66 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-834\nComponents:\n - input (input) params={\"shape\":[1,209]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,209]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":25690,\"embeddingDim\":256}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":256,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[256]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":256,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[256]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":256,\"outFeatures\":66}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 3311-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-836\nComponents:\n - input (input) params={\"shape\":[1,70]}\n - fc1 (linear) params={\"inFeatures\":70,\"outFeatures\":3311}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3311,\"outFeatures\":3311}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3311,\"outFeatures\":3311}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":3311,\"outFeatures\":36}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":70,\"outFeatures\":92}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":92,\"outFeatures\":92}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":92,\"outFeatures\":92}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":92,\"outFeatures\":36}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 88-feature, 30-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-837\nComponents:\n - input (input) params={\"shape\":[1,88]}\n - fc1 (linear) params={\"inFeatures\":88,\"outFeatures\":132}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":132,\"outFeatures\":309}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":309,\"outFeatures\":467}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":467,\"outFeatures\":140}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":140,\"outFeatures\":30}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":132}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":309}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":467}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":140}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 250-feature user input and a 103-feature item input, each through its own 2-layer MLP tower ending at width 62, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-838\nComponents:\n - user_input (input) params={\"shape\":[1,250]}\n - item_input (input) params={\"shape\":[1,103]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,250]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,103]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":250,\"outFeatures\":62}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":62,\"outFeatures\":62}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":103,\"outFeatures\":62}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":62,\"outFeatures\":62}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":124,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (128-feature input, 7 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-839\nComponents:\n - input (input) params={\"shape\":[1,128]}\n - fc1 (linear) params={\"inFeatures\":128,\"outFeatures\":9}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":9,\"outFeatures\":9}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":9,\"outFeatures\":7}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":128,\"outFeatures\":1210}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1210,\"outFeatures\":1210}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1210,\"outFeatures\":7}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 88-feature input with 58 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-840\nComponents:\n - input (input) params={\"shape\":[1,88]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,88]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":88,\"outFeatures\":438}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":438,\"outFeatures\":887}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":887,\"outFeatures\":309}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":309,\"outFeatures\":943}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":943,\"outFeatures\":917}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":917,\"outFeatures\":58}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 295-dim input: encode down to a 66-dim bottleneck and decode back to 295. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-841\nComponents:\n - input (input) params={\"shape\":[1,295]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,295]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":295,\"outFeatures\":119}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":119,\"outFeatures\":66}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":66,\"outFeatures\":119}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":119,\"outFeatures\":295}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x26x26 image with 4 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-842\nComponents:\n - input (input) params={\"shape\":[1,3,26,26]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,26,26]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":32,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":32,\"outChannels\":60,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":60,\"outFeatures\":4}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 223-token sequences with 16 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-843\nComponents:\n - input (input) params={\"shape\":[1,223]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,223]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":35522,\"embeddingDim\":104}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":104,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":104,\"outFeatures\":16}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 227-token sequences with 89 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-844\nComponents:\n - input (input) params={\"shape\":[1,227]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,227]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":15958,\"embeddingDim\":656}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":656,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[656]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":656,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[656]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":656,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[656]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":656,\"outFeatures\":89}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 1649-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-846\nComponents:\n - input (input) params={\"shape\":[1,114]}\n - fc1 (linear) params={\"inFeatures\":114,\"outFeatures\":1649}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":1649,\"outFeatures\":1649}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":1649,\"outFeatures\":1649}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":1649,\"outFeatures\":5}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":114,\"outFeatures\":75}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":75,\"outFeatures\":75}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":75,\"outFeatures\":75}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":75,\"outFeatures\":5}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 36-feature, 28-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-847\nComponents:\n - input (input) params={\"shape\":[1,36]}\n - fc1 (linear) params={\"inFeatures\":36,\"outFeatures\":475}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":475,\"outFeatures\":231}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":231,\"outFeatures\":489}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":489,\"outFeatures\":28}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":475}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":231}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":489}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 240-feature user input and a 165-feature item input, each through its own 2-layer MLP tower ending at width 157, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-848\nComponents:\n - user_input (input) params={\"shape\":[1,240]}\n - item_input (input) params={\"shape\":[1,165]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,240]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,165]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":240,\"outFeatures\":157}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":157,\"outFeatures\":157}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":165,\"outFeatures\":157}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":157,\"outFeatures\":157}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":314,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (69-feature input, 18 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-849\nComponents:\n - input (input) params={\"shape\":[1,69]}\n - fc1 (linear) params={\"inFeatures\":69,\"outFeatures\":23}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":23,\"outFeatures\":23}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":23,\"outFeatures\":18}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":69,\"outFeatures\":1353}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1353,\"outFeatures\":1353}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1353,\"outFeatures\":18}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 88-feature input with 66 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-850\nComponents:\n - input (input) params={\"shape\":[1,88]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,88]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":88,\"outFeatures\":600}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":600,\"outFeatures\":381}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":381,\"outFeatures\":465}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":465,\"outFeatures\":205}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":205,\"outFeatures\":66}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1752-dim input: encode down to a 118-dim bottleneck and decode back to 1752. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-851\nComponents:\n - input (input) params={\"shape\":[1,1752]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1752]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1752,\"outFeatures\":874}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":874,\"outFeatures\":118}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":118,\"outFeatures\":874}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":874,\"outFeatures\":1752}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x53x53 image with 43 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-852\nComponents:\n - input (input) params={\"shape\":[1,3,53,53]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,53,53]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":43,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":43,\"outChannels\":64,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":64,\"outChannels\":14,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":14,\"outFeatures\":43}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 278-token sequences with 45 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-853\nComponents:\n - input (input) params={\"shape\":[1,278]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,278]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":22202,\"embeddingDim\":76}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":76,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":76,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":76,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":76,\"outFeatures\":45}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 488-token sequences with 17 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-854\nComponents:\n - input (input) params={\"shape\":[1,488]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,488]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":14094,\"embeddingDim\":96}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":96,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[96]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":96,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[96]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":96,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[96]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":96,\"outFeatures\":17}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (266) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-855\nComponents:\n - input (input) params={\"shape\":[1,286]}\n - embed (embedding) params={\"numEmbeddings\":16229,\"embeddingDim\":266}\n - attn (multiHeadAttention) params={\"embedDim\":266,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":266,\"outFeatures\":39}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 2527-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-856\nComponents:\n - input (input) params={\"shape\":[1,80]}\n - fc1 (linear) params={\"inFeatures\":80,\"outFeatures\":2527}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2527,\"outFeatures\":2527}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2527,\"outFeatures\":2527}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":2527,\"outFeatures\":2527}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":2527,\"outFeatures\":20}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":80,\"outFeatures\":66}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":66,\"outFeatures\":66}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":66,\"outFeatures\":66}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":66,\"outFeatures\":66}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":66,\"outFeatures\":20}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 57-feature, 81-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-857\nComponents:\n - input (input) params={\"shape\":[1,57]}\n - fc1 (linear) params={\"inFeatures\":57,\"outFeatures\":84}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":84,\"outFeatures\":118}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":118,\"outFeatures\":93}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":93,\"outFeatures\":81}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":84}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":118}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":93}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 86-feature user input and a 88-feature item input, each through its own 2-layer MLP tower ending at width 340, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-858\nComponents:\n - user_input (input) params={\"shape\":[1,86]}\n - item_input (input) params={\"shape\":[1,88]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,86]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,88]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":86,\"outFeatures\":340}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":340,\"outFeatures\":340}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":88,\"outFeatures\":340}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":340,\"outFeatures\":340}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":680,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (118-feature input, 44 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-859\nComponents:\n - input (input) params={\"shape\":[1,118]}\n - fc1 (linear) params={\"inFeatures\":118,\"outFeatures\":22}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":22,\"outFeatures\":22}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":22,\"outFeatures\":44}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":118,\"outFeatures\":1092}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1092,\"outFeatures\":1092}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1092,\"outFeatures\":44}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 275-feature input with 131 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-860\nComponents:\n - input (input) params={\"shape\":[1,275]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,275]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":275,\"outFeatures\":23}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":23,\"outFeatures\":950}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":950,\"outFeatures\":258}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":258,\"outFeatures\":688}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":688,\"outFeatures\":50}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":50,\"outFeatures\":131}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 850-dim input: encode down to a 166-dim bottleneck and decode back to 850. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-861\nComponents:\n - input (input) params={\"shape\":[1,850]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,850]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":850,\"outFeatures\":232}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":232,\"outFeatures\":166}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":166,\"outFeatures\":232}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":232,\"outFeatures\":850}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x47x47 image with 90 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-862\nComponents:\n - input (input) params={\"shape\":[1,3,47,47]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,47,47]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":49,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":49,\"outChannels\":40,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":40,\"outFeatures\":90}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 262-token sequences with 19 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-863\nComponents:\n - input (input) params={\"shape\":[1,262]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,262]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":34160,\"embeddingDim\":280}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":280,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":280,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":280,\"outFeatures\":19}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 289-token sequences with 53 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-864\nComponents:\n - input (input) params={\"shape\":[1,289]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,289]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":48174,\"embeddingDim\":208}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":208,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[208]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":208,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[208]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":208,\"outFeatures\":53}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 1571-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-866\nComponents:\n - input (input) params={\"shape\":[1,241]}\n - fc1 (linear) params={\"inFeatures\":241,\"outFeatures\":1571}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":1571,\"outFeatures\":1571}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":1571,\"outFeatures\":33}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":241,\"outFeatures\":198}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":198,\"outFeatures\":198}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":198,\"outFeatures\":33}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 107-feature, 27-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-867\nComponents:\n - input (input) params={\"shape\":[1,107]}\n - fc1 (linear) params={\"inFeatures\":107,\"outFeatures\":213}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":213,\"outFeatures\":425}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":425,\"outFeatures\":414}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":414,\"outFeatures\":27}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":213}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":425}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":414}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 159-feature user input and a 76-feature item input, each through its own 2-layer MLP tower ending at width 297, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-868\nComponents:\n - user_input (input) params={\"shape\":[1,159]}\n - item_input (input) params={\"shape\":[1,76]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,159]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,76]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":159,\"outFeatures\":297}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":297,\"outFeatures\":297}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":76,\"outFeatures\":297}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":297,\"outFeatures\":297}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":594,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (115-feature input, 33 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-869\nComponents:\n - input (input) params={\"shape\":[1,115]}\n - fc1 (linear) params={\"inFeatures\":115,\"outFeatures\":7}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":7,\"outFeatures\":7}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":7,\"outFeatures\":33}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":115,\"outFeatures\":767}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":767,\"outFeatures\":767}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":767,\"outFeatures\":33}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 228-feature input with 100 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-870\nComponents:\n - input (input) params={\"shape\":[1,228]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,228]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":228,\"outFeatures\":990}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":990,\"outFeatures\":1000}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":1000,\"outFeatures\":419}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":419,\"outFeatures\":68}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":68,\"outFeatures\":155}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":155,\"outFeatures\":644}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":644,\"outFeatures\":100}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 735-dim input: encode down to a 153-dim bottleneck and decode back to 735. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-871\nComponents:\n - input (input) params={\"shape\":[1,735]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,735]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":735,\"outFeatures\":456}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":456,\"outFeatures\":153}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":153,\"outFeatures\":456}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":456,\"outFeatures\":735}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x63x63 image with 80 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-872\nComponents:\n - input (input) params={\"shape\":[1,3,63,63]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,63,63]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":40,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":40,\"outChannels\":15,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":15,\"outFeatures\":80}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 233-token sequences with 12 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-873\nComponents:\n - input (input) params={\"shape\":[1,233]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,233]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":22436,\"embeddingDim\":126}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":126,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":126,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":126,\"outFeatures\":12}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 500-token sequences with 33 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-874\nComponents:\n - input (input) params={\"shape\":[1,500]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,500]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":43455,\"embeddingDim\":640}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":640,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[640]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":640,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[640]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":640,\"outFeatures\":33}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (328) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-875\nComponents:\n - input (input) params={\"shape\":[1,220]}\n - embed (embedding) params={\"numEmbeddings\":15054,\"embeddingDim\":328}\n - attn (multiHeadAttention) params={\"embedDim\":328,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":328,\"outFeatures\":43}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":8}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 2984-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-876\nComponents:\n - input (input) params={\"shape\":[1,117]}\n - fc1 (linear) params={\"inFeatures\":117,\"outFeatures\":2984}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2984,\"outFeatures\":2984}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2984,\"outFeatures\":2984}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":2984,\"outFeatures\":12}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":117,\"outFeatures\":245}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":245,\"outFeatures\":245}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":245,\"outFeatures\":245}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":245,\"outFeatures\":12}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 81-feature, 65-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-877\nComponents:\n - input (input) params={\"shape\":[1,81]}\n - fc1 (linear) params={\"inFeatures\":81,\"outFeatures\":70}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":70,\"outFeatures\":324}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":324,\"outFeatures\":488}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":488,\"outFeatures\":48}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":48,\"outFeatures\":330}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":330,\"outFeatures\":65}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":70}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":324}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":488}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":48}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":330}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 118-feature user input and a 128-feature item input, each through its own 2-layer MLP tower ending at width 297, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-878\nComponents:\n - user_input (input) params={\"shape\":[1,118]}\n - item_input (input) params={\"shape\":[1,128]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,118]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,128]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":118,\"outFeatures\":297}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":297,\"outFeatures\":297}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":128,\"outFeatures\":297}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":297,\"outFeatures\":297}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":594,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (102-feature input, 24 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-879\nComponents:\n - input (input) params={\"shape\":[1,102]}\n - fc1 (linear) params={\"inFeatures\":102,\"outFeatures\":16}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":16,\"outFeatures\":16}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":16,\"outFeatures\":24}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":102,\"outFeatures\":1110}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1110,\"outFeatures\":1110}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1110,\"outFeatures\":24}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 158-feature input with 83 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-880\nComponents:\n - input (input) params={\"shape\":[1,158]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,158]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":158,\"outFeatures\":213}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":213,\"outFeatures\":213}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":213,\"outFeatures\":83}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1858-dim input: encode down to a 82-dim bottleneck and decode back to 1858. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-881\nComponents:\n - input (input) params={\"shape\":[1,1858]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1858]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1858,\"outFeatures\":696}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":696,\"outFeatures\":82}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":82,\"outFeatures\":696}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":696,\"outFeatures\":1858}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x58x58 image with 68 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-882\nComponents:\n - input (input) params={\"shape\":[1,3,58,58]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,58,58]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":63,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":63,\"outChannels\":28,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":28,\"outChannels\":58,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":58,\"outChannels\":24,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":24,\"outFeatures\":68}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 253-token sequences with 79 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-883\nComponents:\n - input (input) params={\"shape\":[1,253]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,253]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":43178,\"embeddingDim\":256}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":256,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":256,\"outFeatures\":79}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 499-token sequences with 12 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-884\nComponents:\n - input (input) params={\"shape\":[1,499]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,499]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":18397,\"embeddingDim\":256}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":256,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[256]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":256,\"outFeatures\":12}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (266) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-885\nComponents:\n - input (input) params={\"shape\":[1,248]}\n - embed (embedding) params={\"numEmbeddings\":45272,\"embeddingDim\":266}\n - attn (multiHeadAttention) params={\"embedDim\":266,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":266,\"outFeatures\":52}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 2829-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-886\nComponents:\n - input (input) params={\"shape\":[1,208]}\n - fc1 (linear) params={\"inFeatures\":208,\"outFeatures\":2829}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2829,\"outFeatures\":2829}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":2829,\"outFeatures\":14}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":208,\"outFeatures\":231}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":231,\"outFeatures\":231}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":231,\"outFeatures\":14}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 129-feature, 80-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-887\nComponents:\n - input (input) params={\"shape\":[1,129]}\n - fc1 (linear) params={\"inFeatures\":129,\"outFeatures\":362}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":362,\"outFeatures\":428}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":428,\"outFeatures\":224}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":224,\"outFeatures\":80}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":362}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":428}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":224}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 169-feature user input and a 134-feature item input, each through its own 2-layer MLP tower ending at width 193, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-888\nComponents:\n - user_input (input) params={\"shape\":[1,169]}\n - item_input (input) params={\"shape\":[1,134]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,169]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,134]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":169,\"outFeatures\":193}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":193,\"outFeatures\":193}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":134,\"outFeatures\":193}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":193,\"outFeatures\":193}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":386,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (87-feature input, 10 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-889\nComponents:\n - input (input) params={\"shape\":[1,87]}\n - fc1 (linear) params={\"inFeatures\":87,\"outFeatures\":19}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":19,\"outFeatures\":19}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":19,\"outFeatures\":10}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":87,\"outFeatures\":981}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":981,\"outFeatures\":981}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":981,\"outFeatures\":10}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 177-feature input with 73 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-890\nComponents:\n - input (input) params={\"shape\":[1,177]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,177]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":177,\"outFeatures\":706}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":706,\"outFeatures\":906}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":906,\"outFeatures\":1003}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":1003,\"outFeatures\":73}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 787-dim input: encode down to a 217-dim bottleneck and decode back to 787. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-891\nComponents:\n - input (input) params={\"shape\":[1,787]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,787]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":787,\"outFeatures\":838}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":838,\"outFeatures\":217}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":217,\"outFeatures\":838}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":838,\"outFeatures\":787}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x43x43 image with 95 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-892\nComponents:\n - input (input) params={\"shape\":[1,3,43,43]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,43,43]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":36,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":36,\"outChannels\":12,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":12,\"outChannels\":13,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":13,\"outFeatures\":95}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 206-token sequences with 70 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-893\nComponents:\n - input (input) params={\"shape\":[1,206]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,206]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":17020,\"embeddingDim\":212}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":212,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":212,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":212,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":212,\"outFeatures\":70}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 298-token sequences with 9 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-894\nComponents:\n - input (input) params={\"shape\":[1,298]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,298]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":18545,\"embeddingDim\":172}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":172,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[172]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":172,\"outFeatures\":9}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 2094-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-896\nComponents:\n - input (input) params={\"shape\":[1,53]}\n - fc1 (linear) params={\"inFeatures\":53,\"outFeatures\":2094}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2094,\"outFeatures\":2094}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2094,\"outFeatures\":2094}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":2094,\"outFeatures\":4}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":53,\"outFeatures\":268}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":268,\"outFeatures\":268}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":268,\"outFeatures\":268}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":268,\"outFeatures\":4}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 41-feature, 32-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-897\nComponents:\n - input (input) params={\"shape\":[1,41]}\n - fc1 (linear) params={\"inFeatures\":41,\"outFeatures\":132}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":132,\"outFeatures\":407}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":407,\"outFeatures\":197}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":197,\"outFeatures\":32}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":132}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":407}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":197}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 112-feature user input and a 255-feature item input, each through its own 2-layer MLP tower ending at width 95, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-898\nComponents:\n - user_input (input) params={\"shape\":[1,112]}\n - item_input (input) params={\"shape\":[1,255]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,112]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,255]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":112,\"outFeatures\":95}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":95,\"outFeatures\":95}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":255,\"outFeatures\":95}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":95,\"outFeatures\":95}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":190,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (17-feature input, 30 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-899\nComponents:\n - input (input) params={\"shape\":[1,17]}\n - fc1 (linear) params={\"inFeatures\":17,\"outFeatures\":19}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":19,\"outFeatures\":19}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":19,\"outFeatures\":30}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":17,\"outFeatures\":792}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":792,\"outFeatures\":792}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":792,\"outFeatures\":30}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 408-feature input with 118 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-900\nComponents:\n - input (input) params={\"shape\":[1,408]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,408]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":408,\"outFeatures\":718}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":718,\"outFeatures\":1018}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":1018,\"outFeatures\":311}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":311,\"outFeatures\":570}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":570,\"outFeatures\":118}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 2000-dim input: encode down to a 29-dim bottleneck and decode back to 2000. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-901\nComponents:\n - input (input) params={\"shape\":[1,2000]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,2000]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":2000,\"outFeatures\":638}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":638,\"outFeatures\":29}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":29,\"outFeatures\":638}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":638,\"outFeatures\":2000}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x47x47 image with 38 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-902\nComponents:\n - input (input) params={\"shape\":[1,3,47,47]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,47,47]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":15,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":15,\"outChannels\":47,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":47,\"outChannels\":29,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":29,\"outFeatures\":38}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 114-token sequences with 90 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-903\nComponents:\n - input (input) params={\"shape\":[1,114]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,114]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":48733,\"embeddingDim\":82}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":82,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":82,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":82,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":82,\"outFeatures\":90}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 289-token sequences with 41 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-904\nComponents:\n - input (input) params={\"shape\":[1,289]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,289]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":33649,\"embeddingDim\":176}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":176,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[176]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":176,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[176]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":176,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[176]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":176,\"outFeatures\":41}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 2384-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-906\nComponents:\n - input (input) params={\"shape\":[1,44]}\n - fc1 (linear) params={\"inFeatures\":44,\"outFeatures\":2384}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2384,\"outFeatures\":2384}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2384,\"outFeatures\":2384}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":2384,\"outFeatures\":2384}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":2384,\"outFeatures\":12}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":44,\"outFeatures\":161}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":161,\"outFeatures\":161}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":161,\"outFeatures\":161}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":161,\"outFeatures\":161}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":161,\"outFeatures\":12}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 60-feature, 21-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-907\nComponents:\n - input (input) params={\"shape\":[1,60]}\n - fc1 (linear) params={\"inFeatures\":60,\"outFeatures\":336}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":336,\"outFeatures\":158}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":158,\"outFeatures\":21}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":336}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":158}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 54-feature user input and a 37-feature item input, each through its own 2-layer MLP tower ending at width 257, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-908\nComponents:\n - user_input (input) params={\"shape\":[1,54]}\n - item_input (input) params={\"shape\":[1,37]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,54]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,37]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":54,\"outFeatures\":257}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":257,\"outFeatures\":257}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":37,\"outFeatures\":257}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":257,\"outFeatures\":257}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":514,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (18-feature input, 2 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-909\nComponents:\n - input (input) params={\"shape\":[1,18]}\n - fc1 (linear) params={\"inFeatures\":18,\"outFeatures\":4}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":4,\"outFeatures\":4}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":4,\"outFeatures\":2}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":18,\"outFeatures\":707}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":707,\"outFeatures\":707}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":707,\"outFeatures\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 143-feature input with 52 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-910\nComponents:\n - input (input) params={\"shape\":[1,143]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,143]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":143,\"outFeatures\":76}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":76,\"outFeatures\":373}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":373,\"outFeatures\":550}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":550,\"outFeatures\":911}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":911,\"outFeatures\":52}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1992-dim input: encode down to a 148-dim bottleneck and decode back to 1992. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-911\nComponents:\n - input (input) params={\"shape\":[1,1992]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1992]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1992,\"outFeatures\":503}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":503,\"outFeatures\":148}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":148,\"outFeatures\":503}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":503,\"outFeatures\":1992}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x52x52 image with 86 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-912\nComponents:\n - input (input) params={\"shape\":[1,3,52,52]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,52,52]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":29,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":29,\"outChannels\":33,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":33,\"outChannels\":34,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":34,\"outFeatures\":86}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 431-token sequences with 87 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-913\nComponents:\n - input (input) params={\"shape\":[1,431]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,431]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":14744,\"embeddingDim\":68}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":68,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":68,\"outFeatures\":87}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 47-token sequences with 7 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-914\nComponents:\n - input (input) params={\"shape\":[1,47]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,47]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":17429,\"embeddingDim\":92}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":92,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[92]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":92,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[92]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":92,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[92]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":92,\"outFeatures\":7}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (156) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-915\nComponents:\n - input (input) params={\"shape\":[1,135]}\n - embed (embedding) params={\"numEmbeddings\":25737,\"embeddingDim\":156}\n - attn (multiHeadAttention) params={\"embedDim\":156,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":156,\"outFeatures\":89}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":4}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 2570-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-916\nComponents:\n - input (input) params={\"shape\":[1,127]}\n - fc1 (linear) params={\"inFeatures\":127,\"outFeatures\":2570}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2570,\"outFeatures\":2570}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2570,\"outFeatures\":2570}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":2570,\"outFeatures\":32}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":127,\"outFeatures\":383}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":383,\"outFeatures\":383}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":383,\"outFeatures\":383}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":383,\"outFeatures\":32}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 166-feature, 49-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-917\nComponents:\n - input (input) params={\"shape\":[1,166]}\n - fc1 (linear) params={\"inFeatures\":166,\"outFeatures\":473}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":473,\"outFeatures\":153}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":153,\"outFeatures\":49}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":473}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":153}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 217-feature user input and a 26-feature item input, each through its own 2-layer MLP tower ending at width 183, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-918\nComponents:\n - user_input (input) params={\"shape\":[1,217]}\n - item_input (input) params={\"shape\":[1,26]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,217]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,26]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":217,\"outFeatures\":183}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":183,\"outFeatures\":183}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":26,\"outFeatures\":183}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":183,\"outFeatures\":183}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":366,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (76-feature input, 40 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-919\nComponents:\n - input (input) params={\"shape\":[1,76]}\n - fc1 (linear) params={\"inFeatures\":76,\"outFeatures\":4}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":4,\"outFeatures\":4}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":4,\"outFeatures\":40}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":76,\"outFeatures\":1348}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1348,\"outFeatures\":1348}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1348,\"outFeatures\":40}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 405-feature input with 6 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-920\nComponents:\n - input (input) params={\"shape\":[1,405]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,405]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":405,\"outFeatures\":153}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":153,\"outFeatures\":595}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":595,\"outFeatures\":524}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":524,\"outFeatures\":6}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 728-dim input: encode down to a 127-dim bottleneck and decode back to 728. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-921\nComponents:\n - input (input) params={\"shape\":[1,728]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,728]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":728,\"outFeatures\":686}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":686,\"outFeatures\":127}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":127,\"outFeatures\":686}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":686,\"outFeatures\":728}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x38x38 image with 95 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-922\nComponents:\n - input (input) params={\"shape\":[1,3,38,38]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,38,38]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":46,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":46,\"outChannels\":18,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":18,\"outFeatures\":95}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 200-token sequences with 53 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-923\nComponents:\n - input (input) params={\"shape\":[1,200]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,200]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":35697,\"embeddingDim\":56}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":56,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":56,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":56,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":56,\"outFeatures\":53}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 375-token sequences with 14 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-924\nComponents:\n - input (input) params={\"shape\":[1,375]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,375]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":20572,\"embeddingDim\":328}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":328,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[328]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":328,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[328]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":328,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[328]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":328,\"outFeatures\":14}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (162) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-925\nComponents:\n - input (input) params={\"shape\":[1,470]}\n - embed (embedding) params={\"numEmbeddings\":31222,\"embeddingDim\":162}\n - attn (multiHeadAttention) params={\"embedDim\":162,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":162,\"outFeatures\":65}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3735-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-926\nComponents:\n - input (input) params={\"shape\":[1,162]}\n - fc1 (linear) params={\"inFeatures\":162,\"outFeatures\":3735}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3735,\"outFeatures\":3735}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3735,\"outFeatures\":3735}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3735,\"outFeatures\":3735}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3735,\"outFeatures\":35}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":162,\"outFeatures\":70}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":70,\"outFeatures\":70}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":70,\"outFeatures\":70}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":70,\"outFeatures\":70}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":70,\"outFeatures\":35}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 23-feature, 64-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-927\nComponents:\n - input (input) params={\"shape\":[1,23]}\n - fc1 (linear) params={\"inFeatures\":23,\"outFeatures\":490}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":490,\"outFeatures\":146}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":146,\"outFeatures\":373}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":373,\"outFeatures\":348}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":348,\"outFeatures\":64}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":490}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":146}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":373}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":348}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 75-feature user input and a 241-feature item input, each through its own 2-layer MLP tower ending at width 136, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-928\nComponents:\n - user_input (input) params={\"shape\":[1,75]}\n - item_input (input) params={\"shape\":[1,241]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,75]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,241]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":75,\"outFeatures\":136}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":136,\"outFeatures\":136}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":241,\"outFeatures\":136}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":136,\"outFeatures\":136}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":272,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (90-feature input, 44 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-929\nComponents:\n - input (input) params={\"shape\":[1,90]}\n - fc1 (linear) params={\"inFeatures\":90,\"outFeatures\":24}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":24,\"outFeatures\":24}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":24,\"outFeatures\":44}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":90,\"outFeatures\":690}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":690,\"outFeatures\":690}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":690,\"outFeatures\":44}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 288-feature input with 46 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-930\nComponents:\n - input (input) params={\"shape\":[1,288]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,288]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":288,\"outFeatures\":572}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":572,\"outFeatures\":126}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":126,\"outFeatures\":89}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":89,\"outFeatures\":84}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":84,\"outFeatures\":46}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1573-dim input: encode down to a 170-dim bottleneck and decode back to 1573. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-931\nComponents:\n - input (input) params={\"shape\":[1,1573]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1573]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1573,\"outFeatures\":243}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":243,\"outFeatures\":170}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":170,\"outFeatures\":243}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":243,\"outFeatures\":1573}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x43x43 image with 69 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-932\nComponents:\n - input (input) params={\"shape\":[1,3,43,43]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,43,43]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":63,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":63,\"outChannels\":37,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":37,\"outChannels\":13,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":13,\"outFeatures\":69}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 35-token sequences with 77 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-933\nComponents:\n - input (input) params={\"shape\":[1,35]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,35]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":44795,\"embeddingDim\":104}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":104,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":104,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":104,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":104,\"outFeatures\":77}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 456-token sequences with 34 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-934\nComponents:\n - input (input) params={\"shape\":[1,456]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,456]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":39599,\"embeddingDim\":144}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":144,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[144]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":144,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[144]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":144,\"outFeatures\":34}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (94) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-935\nComponents:\n - input (input) params={\"shape\":[1,445]}\n - embed (embedding) params={\"numEmbeddings\":26183,\"embeddingDim\":94}\n - attn (multiHeadAttention) params={\"embedDim\":94,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":94,\"outFeatures\":31}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 1738-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-936\nComponents:\n - input (input) params={\"shape\":[1,94]}\n - fc1 (linear) params={\"inFeatures\":94,\"outFeatures\":1738}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":1738,\"outFeatures\":1738}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":1738,\"outFeatures\":1738}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":1738,\"outFeatures\":1738}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":1738,\"outFeatures\":30}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":94,\"outFeatures\":92}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":92,\"outFeatures\":92}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":92,\"outFeatures\":92}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":92,\"outFeatures\":92}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":92,\"outFeatures\":30}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 145-feature, 87-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-937\nComponents:\n - input (input) params={\"shape\":[1,145]}\n - fc1 (linear) params={\"inFeatures\":145,\"outFeatures\":66}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":66,\"outFeatures\":509}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":509,\"outFeatures\":119}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":119,\"outFeatures\":280}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":280,\"outFeatures\":59}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":59,\"outFeatures\":87}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":66}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":509}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":119}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":280}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":59}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 57-feature user input and a 238-feature item input, each through its own 2-layer MLP tower ending at width 297, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-938\nComponents:\n - user_input (input) params={\"shape\":[1,57]}\n - item_input (input) params={\"shape\":[1,238]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,57]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,238]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":57,\"outFeatures\":297}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":297,\"outFeatures\":297}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":238,\"outFeatures\":297}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":297,\"outFeatures\":297}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":594,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (116-feature input, 49 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-939\nComponents:\n - input (input) params={\"shape\":[1,116]}\n - fc1 (linear) params={\"inFeatures\":116,\"outFeatures\":22}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":22,\"outFeatures\":22}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":22,\"outFeatures\":49}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":116,\"outFeatures\":1305}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1305,\"outFeatures\":1305}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1305,\"outFeatures\":49}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 505-feature input with 160 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-940\nComponents:\n - input (input) params={\"shape\":[1,505]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,505]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":505,\"outFeatures\":122}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":122,\"outFeatures\":913}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":913,\"outFeatures\":913}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":913,\"outFeatures\":673}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":673,\"outFeatures\":160}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1050-dim input: encode down to a 142-dim bottleneck and decode back to 1050. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-941\nComponents:\n - input (input) params={\"shape\":[1,1050]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1050]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1050,\"outFeatures\":270}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":270,\"outFeatures\":142}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":142,\"outFeatures\":270}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":270,\"outFeatures\":1050}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x50x50 image with 6 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-942\nComponents:\n - input (input) params={\"shape\":[1,3,50,50]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,50,50]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":63,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":63,\"outChannels\":35,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":35,\"outChannels\":36,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":36,\"outChannels\":58,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":58,\"outFeatures\":6}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 408-token sequences with 98 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-943\nComponents:\n - input (input) params={\"shape\":[1,408]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,408]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":13806,\"embeddingDim\":360}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":360,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":360,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":360,\"outFeatures\":98}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 227-token sequences with 94 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-944\nComponents:\n - input (input) params={\"shape\":[1,227]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,227]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":34234,\"embeddingDim\":72}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":72,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[72]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":72,\"outFeatures\":94}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (480) is not divisible by numHeads (7). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-945\nComponents:\n - input (input) params={\"shape\":[1,251]}\n - embed (embedding) params={\"numEmbeddings\":29693,\"embeddingDim\":480}\n - attn (multiHeadAttention) params={\"embedDim\":480,\"numHeads\":7}\n - head (linear) params={\"inFeatures\":480,\"outFeatures\":47}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":16}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 2672-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-946\nComponents:\n - input (input) params={\"shape\":[1,190]}\n - fc1 (linear) params={\"inFeatures\":190,\"outFeatures\":2672}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2672,\"outFeatures\":2672}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2672,\"outFeatures\":2672}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":2672,\"outFeatures\":2672}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":2672,\"outFeatures\":50}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":190,\"outFeatures\":321}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":321,\"outFeatures\":321}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":321,\"outFeatures\":321}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":321,\"outFeatures\":321}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":321,\"outFeatures\":50}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 118-feature, 82-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-947\nComponents:\n - input (input) params={\"shape\":[1,118]}\n - fc1 (linear) params={\"inFeatures\":118,\"outFeatures\":471}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":471,\"outFeatures\":147}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":147,\"outFeatures\":116}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":116,\"outFeatures\":82}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":471}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":147}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":116}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 158-feature user input and a 185-feature item input, each through its own 2-layer MLP tower ending at width 390, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-948\nComponents:\n - user_input (input) params={\"shape\":[1,158]}\n - item_input (input) params={\"shape\":[1,185]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,158]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,185]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":158,\"outFeatures\":390}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":390,\"outFeatures\":390}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":185,\"outFeatures\":390}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":390,\"outFeatures\":390}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":780,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (127-feature input, 47 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-949\nComponents:\n - input (input) params={\"shape\":[1,127]}\n - fc1 (linear) params={\"inFeatures\":127,\"outFeatures\":16}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":16,\"outFeatures\":16}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":16,\"outFeatures\":47}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":127,\"outFeatures\":1109}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1109,\"outFeatures\":1109}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1109,\"outFeatures\":47}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 460-feature input with 197 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-950\nComponents:\n - input (input) params={\"shape\":[1,460]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,460]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":460,\"outFeatures\":856}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":856,\"outFeatures\":239}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":239,\"outFeatures\":812}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":812,\"outFeatures\":488}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":488,\"outFeatures\":731}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":731,\"outFeatures\":197}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 806-dim input: encode down to a 60-dim bottleneck and decode back to 806. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-951\nComponents:\n - input (input) params={\"shape\":[1,806]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,806]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":806,\"outFeatures\":1016}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":1016,\"outFeatures\":60}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":60,\"outFeatures\":1016}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":1016,\"outFeatures\":806}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x57x57 image with 65 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-952\nComponents:\n - input (input) params={\"shape\":[1,3,57,57]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,57,57]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":50,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":50,\"outChannels\":53,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":53,\"outChannels\":32,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":32,\"outFeatures\":65}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 156-token sequences with 3 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-953\nComponents:\n - input (input) params={\"shape\":[1,156]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,156]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":34497,\"embeddingDim\":48}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":48,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":48,\"outFeatures\":3}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 447-token sequences with 53 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-954\nComponents:\n - input (input) params={\"shape\":[1,447]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,447]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":34821,\"embeddingDim\":336}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":336,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[336]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":336,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[336]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":336,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[336]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":336,\"outFeatures\":53}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (158) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-955\nComponents:\n - input (input) params={\"shape\":[1,468]}\n - embed (embedding) params={\"numEmbeddings\":30163,\"embeddingDim\":158}\n - attn (multiHeadAttention) params={\"embedDim\":158,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":158,\"outFeatures\":38}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 2326-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-956\nComponents:\n - input (input) params={\"shape\":[1,189]}\n - fc1 (linear) params={\"inFeatures\":189,\"outFeatures\":2326}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2326,\"outFeatures\":2326}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2326,\"outFeatures\":2326}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":2326,\"outFeatures\":2326}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":2326,\"outFeatures\":19}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":189,\"outFeatures\":369}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":369,\"outFeatures\":369}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":369,\"outFeatures\":369}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":369,\"outFeatures\":369}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":369,\"outFeatures\":19}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 97-feature, 16-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-957\nComponents:\n - input (input) params={\"shape\":[1,97]}\n - fc1 (linear) params={\"inFeatures\":97,\"outFeatures\":427}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":427,\"outFeatures\":172}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":172,\"outFeatures\":489}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":489,\"outFeatures\":392}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":392,\"outFeatures\":16}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":427}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":172}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":489}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":392}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 86-feature user input and a 17-feature item input, each through its own 2-layer MLP tower ending at width 168, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-958\nComponents:\n - user_input (input) params={\"shape\":[1,86]}\n - item_input (input) params={\"shape\":[1,17]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,86]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,17]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":86,\"outFeatures\":168}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":168,\"outFeatures\":168}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":17,\"outFeatures\":168}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":168,\"outFeatures\":168}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":336,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (20-feature input, 46 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-959\nComponents:\n - input (input) params={\"shape\":[1,20]}\n - fc1 (linear) params={\"inFeatures\":20,\"outFeatures\":11}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":11,\"outFeatures\":11}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":11,\"outFeatures\":46}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":20,\"outFeatures\":1036}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1036,\"outFeatures\":1036}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1036,\"outFeatures\":46}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 314-feature input with 40 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-960\nComponents:\n - input (input) params={\"shape\":[1,314]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,314]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":314,\"outFeatures\":37}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":37,\"outFeatures\":246}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":246,\"outFeatures\":20}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":20,\"outFeatures\":76}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":76,\"outFeatures\":704}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":704,\"outFeatures\":692}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":692,\"outFeatures\":40}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1087-dim input: encode down to a 195-dim bottleneck and decode back to 1087. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-961\nComponents:\n - input (input) params={\"shape\":[1,1087]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1087]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1087,\"outFeatures\":685}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":685,\"outFeatures\":195}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":195,\"outFeatures\":685}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":685,\"outFeatures\":1087}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x43x43 image with 5 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-962\nComponents:\n - input (input) params={\"shape\":[1,3,43,43]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,43,43]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":24,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":24,\"outChannels\":64,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":64,\"outChannels\":47,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":47,\"outFeatures\":5}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 74-token sequences with 33 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-963\nComponents:\n - input (input) params={\"shape\":[1,74]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,74]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":17846,\"embeddingDim\":180}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":180,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":180,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":180,\"outFeatures\":33}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 355-token sequences with 37 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-964\nComponents:\n - input (input) params={\"shape\":[1,355]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,355]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":39601,\"embeddingDim\":224}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":224,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[224]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":224,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[224]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":224,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[224]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":224,\"outFeatures\":37}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (92) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-965\nComponents:\n - input (input) params={\"shape\":[1,124]}\n - embed (embedding) params={\"numEmbeddings\":32853,\"embeddingDim\":92}\n - attn (multiHeadAttention) params={\"embedDim\":92,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":92,\"outFeatures\":70}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":4}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 3446-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-966\nComponents:\n - input (input) params={\"shape\":[1,54]}\n - fc1 (linear) params={\"inFeatures\":54,\"outFeatures\":3446}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3446,\"outFeatures\":3446}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3446,\"outFeatures\":3446}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":3446,\"outFeatures\":37}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":54,\"outFeatures\":99}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":99,\"outFeatures\":99}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":99,\"outFeatures\":99}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":99,\"outFeatures\":37}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 53-feature, 74-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-967\nComponents:\n - input (input) params={\"shape\":[1,53]}\n - fc1 (linear) params={\"inFeatures\":53,\"outFeatures\":193}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":193,\"outFeatures\":449}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":449,\"outFeatures\":224}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":224,\"outFeatures\":504}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":504,\"outFeatures\":360}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":360,\"outFeatures\":74}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":193}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":449}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":224}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":504}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":360}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 242-feature user input and a 147-feature item input, each through its own 2-layer MLP tower ending at width 411, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-968\nComponents:\n - user_input (input) params={\"shape\":[1,242]}\n - item_input (input) params={\"shape\":[1,147]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,242]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,147]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":242,\"outFeatures\":411}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":411,\"outFeatures\":411}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":147,\"outFeatures\":411}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":411,\"outFeatures\":411}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":822,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (30-feature input, 14 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-969\nComponents:\n - input (input) params={\"shape\":[1,30]}\n - fc1 (linear) params={\"inFeatures\":30,\"outFeatures\":5}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":5,\"outFeatures\":5}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":5,\"outFeatures\":14}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":30,\"outFeatures\":957}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":957,\"outFeatures\":957}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":957,\"outFeatures\":14}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 487-feature input with 73 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-970\nComponents:\n - input (input) params={\"shape\":[1,487]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,487]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":487,\"outFeatures\":398}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":398,\"outFeatures\":581}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":581,\"outFeatures\":73}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 872-dim input: encode down to a 175-dim bottleneck and decode back to 872. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-971\nComponents:\n - input (input) params={\"shape\":[1,872]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,872]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":872,\"outFeatures\":804}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":804,\"outFeatures\":175}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":175,\"outFeatures\":804}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":804,\"outFeatures\":872}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x26x26 image with 60 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-972\nComponents:\n - input (input) params={\"shape\":[1,3,26,26]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,26,26]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":63,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":63,\"outChannels\":61,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":61,\"outChannels\":24,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":24,\"outFeatures\":60}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 418-token sequences with 6 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-973\nComponents:\n - input (input) params={\"shape\":[1,418]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,418]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":41776,\"embeddingDim\":488}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":488,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":488,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":488,\"outFeatures\":6}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 175-token sequences with 4 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-974\nComponents:\n - input (input) params={\"shape\":[1,175]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,175]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":35575,\"embeddingDim\":240}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":240,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[240]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":240,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[240]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":240,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[240]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":240,\"outFeatures\":4}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 3644-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-976\nComponents:\n - input (input) params={\"shape\":[1,149]}\n - fc1 (linear) params={\"inFeatures\":149,\"outFeatures\":3644}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3644,\"outFeatures\":3644}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":3644,\"outFeatures\":24}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":149,\"outFeatures\":371}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":371,\"outFeatures\":371}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":371,\"outFeatures\":24}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 68-feature, 85-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-977\nComponents:\n - input (input) params={\"shape\":[1,68]}\n - fc1 (linear) params={\"inFeatures\":68,\"outFeatures\":296}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":296,\"outFeatures\":229}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":229,\"outFeatures\":402}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":402,\"outFeatures\":246}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":246,\"outFeatures\":398}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":398,\"outFeatures\":85}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":296}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":229}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":402}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":246}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":398}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 39-feature user input and a 119-feature item input, each through its own 2-layer MLP tower ending at width 458, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-978\nComponents:\n - user_input (input) params={\"shape\":[1,39]}\n - item_input (input) params={\"shape\":[1,119]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,39]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,119]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":39,\"outFeatures\":458}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":458,\"outFeatures\":458}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":119,\"outFeatures\":458}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":458,\"outFeatures\":458}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":916,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (71-feature input, 20 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-979\nComponents:\n - input (input) params={\"shape\":[1,71]}\n - fc1 (linear) params={\"inFeatures\":71,\"outFeatures\":5}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":5,\"outFeatures\":5}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":5,\"outFeatures\":20}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":71,\"outFeatures\":751}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":751,\"outFeatures\":751}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":751,\"outFeatures\":20}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 438-feature input with 118 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-980\nComponents:\n - input (input) params={\"shape\":[1,438]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,438]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":438,\"outFeatures\":886}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":886,\"outFeatures\":417}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":417,\"outFeatures\":277}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":277,\"outFeatures\":266}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":266,\"outFeatures\":321}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":321,\"outFeatures\":658}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":658,\"outFeatures\":118}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1010-dim input: encode down to a 47-dim bottleneck and decode back to 1010. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-981\nComponents:\n - input (input) params={\"shape\":[1,1010]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1010]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1010,\"outFeatures\":319}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":319,\"outFeatures\":47}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":47,\"outFeatures\":319}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":319,\"outFeatures\":1010}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x50x50 image with 47 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-982\nComponents:\n - input (input) params={\"shape\":[1,3,50,50]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,50,50]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":59,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":59,\"outChannels\":41,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":41,\"outChannels\":8,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":8,\"outChannels\":42,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":42,\"outFeatures\":47}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 174-token sequences with 49 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-983\nComponents:\n - input (input) params={\"shape\":[1,174]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,174]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":14994,\"embeddingDim\":256}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":256,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":256,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":256,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":256,\"outFeatures\":49}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 281-token sequences with 33 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-984\nComponents:\n - input (input) params={\"shape\":[1,281]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,281]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":12424,\"embeddingDim\":40}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":40,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[40]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":40,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[40]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":40,\"outFeatures\":33}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 1597-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-986\nComponents:\n - input (input) params={\"shape\":[1,134]}\n - fc1 (linear) params={\"inFeatures\":134,\"outFeatures\":1597}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":1597,\"outFeatures\":1597}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":1597,\"outFeatures\":43}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":134,\"outFeatures\":271}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":271,\"outFeatures\":271}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":271,\"outFeatures\":43}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 252-feature, 21-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-987\nComponents:\n - input (input) params={\"shape\":[1,252]}\n - fc1 (linear) params={\"inFeatures\":252,\"outFeatures\":128}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":128,\"outFeatures\":120}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":120,\"outFeatures\":511}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":511,\"outFeatures\":412}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":412,\"outFeatures\":21}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":128}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":120}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":511}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":412}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 167-feature user input and a 201-feature item input, each through its own 2-layer MLP tower ending at width 133, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-988\nComponents:\n - user_input (input) params={\"shape\":[1,167]}\n - item_input (input) params={\"shape\":[1,201]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,167]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,201]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":167,\"outFeatures\":133}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":133,\"outFeatures\":133}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":201,\"outFeatures\":133}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":133,\"outFeatures\":133}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":266,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (42-feature input, 8 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-989\nComponents:\n - input (input) params={\"shape\":[1,42]}\n - fc1 (linear) params={\"inFeatures\":42,\"outFeatures\":5}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":5,\"outFeatures\":5}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":5,\"outFeatures\":8}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":42,\"outFeatures\":737}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":737,\"outFeatures\":737}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":737,\"outFeatures\":8}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 445-feature input with 60 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-990\nComponents:\n - input (input) params={\"shape\":[1,445]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,445]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":445,\"outFeatures\":511}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":511,\"outFeatures\":825}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":825,\"outFeatures\":1017}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":1017,\"outFeatures\":23}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":23,\"outFeatures\":60}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1284-dim input: encode down to a 233-dim bottleneck and decode back to 1284. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-991\nComponents:\n - input (input) params={\"shape\":[1,1284]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1284]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1284,\"outFeatures\":650}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":650,\"outFeatures\":233}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":233,\"outFeatures\":650}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":650,\"outFeatures\":1284}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x61x61 image with 56 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-992\nComponents:\n - input (input) params={\"shape\":[1,3,61,61]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,61,61]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":37,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":37,\"outChannels\":37,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":37,\"outChannels\":29,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":29,\"outChannels\":33,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":33,\"outFeatures\":56}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 464-token sequences with 28 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-993\nComponents:\n - input (input) params={\"shape\":[1,464]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,464]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":21847,\"embeddingDim\":200}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":200,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":200,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":200,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":200,\"outFeatures\":28}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 295-token sequences with 60 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-994\nComponents:\n - input (input) params={\"shape\":[1,295]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,295]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":24955,\"embeddingDim\":288}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":288,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[288]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":288,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[288]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":288,\"outFeatures\":60}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 2810-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-996\nComponents:\n - input (input) params={\"shape\":[1,217]}\n - fc1 (linear) params={\"inFeatures\":217,\"outFeatures\":2810}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2810,\"outFeatures\":2810}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2810,\"outFeatures\":2810}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":2810,\"outFeatures\":32}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":217,\"outFeatures\":303}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":303,\"outFeatures\":303}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":303,\"outFeatures\":303}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":303,\"outFeatures\":32}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 120-feature, 79-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-997\nComponents:\n - input (input) params={\"shape\":[1,120]}\n - fc1 (linear) params={\"inFeatures\":120,\"outFeatures\":177}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":177,\"outFeatures\":44}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":44,\"outFeatures\":393}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":393,\"outFeatures\":79}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":177}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":44}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":393}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 219-feature user input and a 189-feature item input, each through its own 2-layer MLP tower ending at width 461, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-998\nComponents:\n - user_input (input) params={\"shape\":[1,219]}\n - item_input (input) params={\"shape\":[1,189]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,219]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,189]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":219,\"outFeatures\":461}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":461,\"outFeatures\":461}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":189,\"outFeatures\":461}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":461,\"outFeatures\":461}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":922,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (63-feature input, 11 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-999\nComponents:\n - input (input) params={\"shape\":[1,63]}\n - fc1 (linear) params={\"inFeatures\":63,\"outFeatures\":18}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":18,\"outFeatures\":18}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":18,\"outFeatures\":11}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":63,\"outFeatures\":755}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":755,\"outFeatures\":755}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":755,\"outFeatures\":11}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 40-feature input with 16 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1000\nComponents:\n - input (input) params={\"shape\":[1,40]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,40]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":40,\"outFeatures\":84}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":84,\"outFeatures\":788}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":788,\"outFeatures\":265}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":265,\"outFeatures\":744}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":744,\"outFeatures\":506}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":506,\"outFeatures\":16}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 192-dim input: encode down to a 10-dim bottleneck and decode back to 192. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1001\nComponents:\n - input (input) params={\"shape\":[1,192]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,192]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":192,\"outFeatures\":198}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":198,\"outFeatures\":10}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":10,\"outFeatures\":198}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":198,\"outFeatures\":192}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x37x37 image with 24 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1002\nComponents:\n - input (input) params={\"shape\":[1,3,37,37]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,37,37]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":43,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":43,\"outChannels\":11,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":11,\"outChannels\":41,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":41,\"outChannels\":32,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":32,\"outFeatures\":24}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 484-token sequences with 78 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1003\nComponents:\n - input (input) params={\"shape\":[1,484]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,484]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":32207,\"embeddingDim\":82}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":82,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":82,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":82,\"outFeatures\":78}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 478-token sequences with 27 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1004\nComponents:\n - input (input) params={\"shape\":[1,478]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,478]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":34660,\"embeddingDim\":480}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":480,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[480]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":480,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[480]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":480,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[480]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":480,\"outFeatures\":27}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 3701-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1006\nComponents:\n - input (input) params={\"shape\":[1,41]}\n - fc1 (linear) params={\"inFeatures\":41,\"outFeatures\":3701}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3701,\"outFeatures\":3701}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":3701,\"outFeatures\":27}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":41,\"outFeatures\":338}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":338,\"outFeatures\":338}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":338,\"outFeatures\":27}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 124-feature, 44-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1007\nComponents:\n - input (input) params={\"shape\":[1,124]}\n - fc1 (linear) params={\"inFeatures\":124,\"outFeatures\":88}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":88,\"outFeatures\":244}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":244,\"outFeatures\":44}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":88}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":244}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 61-feature user input and a 28-feature item input, each through its own 2-layer MLP tower ending at width 55, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1008\nComponents:\n - user_input (input) params={\"shape\":[1,61]}\n - item_input (input) params={\"shape\":[1,28]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,61]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,28]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":61,\"outFeatures\":55}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":55,\"outFeatures\":55}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":28,\"outFeatures\":55}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":55,\"outFeatures\":55}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":110,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (119-feature input, 34 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1009\nComponents:\n - input (input) params={\"shape\":[1,119]}\n - fc1 (linear) params={\"inFeatures\":119,\"outFeatures\":6}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":6,\"outFeatures\":6}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":6,\"outFeatures\":34}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":119,\"outFeatures\":1123}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1123,\"outFeatures\":1123}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1123,\"outFeatures\":34}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 477-feature input with 103 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1010\nComponents:\n - input (input) params={\"shape\":[1,477]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,477]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":477,\"outFeatures\":585}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":585,\"outFeatures\":484}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":484,\"outFeatures\":21}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":21,\"outFeatures\":103}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1989-dim input: encode down to a 25-dim bottleneck and decode back to 1989. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1011\nComponents:\n - input (input) params={\"shape\":[1,1989]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1989]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1989,\"outFeatures\":534}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":534,\"outFeatures\":25}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":25,\"outFeatures\":534}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":534,\"outFeatures\":1989}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x36x36 image with 59 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1012\nComponents:\n - input (input) params={\"shape\":[1,3,36,36]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,36,36]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":46,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":46,\"outChannels\":60,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":60,\"outChannels\":50,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":50,\"outChannels\":29,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":29,\"outFeatures\":59}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 221-token sequences with 86 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1013\nComponents:\n - input (input) params={\"shape\":[1,221]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,221]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":43254,\"embeddingDim\":116}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":116,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":116,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":116,\"outFeatures\":86}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 357-token sequences with 23 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1014\nComponents:\n - input (input) params={\"shape\":[1,357]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,357]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":22842,\"embeddingDim\":160}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":160,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[160]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":160,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[160]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":160,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[160]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":160,\"outFeatures\":23}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 2095-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1016\nComponents:\n - input (input) params={\"shape\":[1,80]}\n - fc1 (linear) params={\"inFeatures\":80,\"outFeatures\":2095}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2095,\"outFeatures\":2095}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2095,\"outFeatures\":2095}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":2095,\"outFeatures\":11}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":80,\"outFeatures\":276}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":276,\"outFeatures\":276}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":276,\"outFeatures\":276}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":276,\"outFeatures\":11}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 181-feature, 78-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1017\nComponents:\n - input (input) params={\"shape\":[1,181]}\n - fc1 (linear) params={\"inFeatures\":181,\"outFeatures\":150}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":150,\"outFeatures\":440}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":440,\"outFeatures\":78}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":150}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":440}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 238-feature user input and a 250-feature item input, each through its own 2-layer MLP tower ending at width 362, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1018\nComponents:\n - user_input (input) params={\"shape\":[1,238]}\n - item_input (input) params={\"shape\":[1,250]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,238]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,250]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":238,\"outFeatures\":362}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":362,\"outFeatures\":362}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":250,\"outFeatures\":362}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":362,\"outFeatures\":362}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":724,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (49-feature input, 43 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1019\nComponents:\n - input (input) params={\"shape\":[1,49]}\n - fc1 (linear) params={\"inFeatures\":49,\"outFeatures\":15}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":15,\"outFeatures\":15}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":15,\"outFeatures\":43}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":49,\"outFeatures\":982}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":982,\"outFeatures\":982}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":982,\"outFeatures\":43}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 127-feature input with 155 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1020\nComponents:\n - input (input) params={\"shape\":[1,127]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,127]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":127,\"outFeatures\":242}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":242,\"outFeatures\":229}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":229,\"outFeatures\":208}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":208,\"outFeatures\":892}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":892,\"outFeatures\":895}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":895,\"outFeatures\":643}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":643,\"outFeatures\":155}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 697-dim input: encode down to a 174-dim bottleneck and decode back to 697. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1021\nComponents:\n - input (input) params={\"shape\":[1,697]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,697]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":697,\"outFeatures\":837}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":837,\"outFeatures\":174}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":174,\"outFeatures\":837}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":837,\"outFeatures\":697}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x59x59 image with 69 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1022\nComponents:\n - input (input) params={\"shape\":[1,3,59,59]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,59,59]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":54,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":54,\"outChannels\":37,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":37,\"outFeatures\":69}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 207-token sequences with 59 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1023\nComponents:\n - input (input) params={\"shape\":[1,207]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,207]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":10173,\"embeddingDim\":192}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":192,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":192,\"outFeatures\":59}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 236-token sequences with 38 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1024\nComponents:\n - input (input) params={\"shape\":[1,236]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,236]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":8543,\"embeddingDim\":160}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":160,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[160]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":160,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[160]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":160,\"outFeatures\":38}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 3796-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1026\nComponents:\n - input (input) params={\"shape\":[1,213]}\n - fc1 (linear) params={\"inFeatures\":213,\"outFeatures\":3796}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3796,\"outFeatures\":3796}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":3796,\"outFeatures\":16}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":213,\"outFeatures\":129}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":129,\"outFeatures\":129}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":129,\"outFeatures\":16}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 76-feature, 94-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1027\nComponents:\n - input (input) params={\"shape\":[1,76]}\n - fc1 (linear) params={\"inFeatures\":76,\"outFeatures\":491}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":491,\"outFeatures\":194}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":194,\"outFeatures\":94}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":491}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":194}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 63-feature user input and a 149-feature item input, each through its own 2-layer MLP tower ending at width 40, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1028\nComponents:\n - user_input (input) params={\"shape\":[1,63]}\n - item_input (input) params={\"shape\":[1,149]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,63]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,149]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":63,\"outFeatures\":40}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":40,\"outFeatures\":40}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":149,\"outFeatures\":40}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":40,\"outFeatures\":40}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":80,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (117-feature input, 26 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1029\nComponents:\n - input (input) params={\"shape\":[1,117]}\n - fc1 (linear) params={\"inFeatures\":117,\"outFeatures\":12}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":12,\"outFeatures\":12}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":12,\"outFeatures\":26}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":117,\"outFeatures\":670}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":670,\"outFeatures\":670}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":670,\"outFeatures\":26}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 78-feature input with 146 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1030\nComponents:\n - input (input) params={\"shape\":[1,78]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,78]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":78,\"outFeatures\":420}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":420,\"outFeatures\":182}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":182,\"outFeatures\":762}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":762,\"outFeatures\":614}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":614,\"outFeatures\":316}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":316,\"outFeatures\":146}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1265-dim input: encode down to a 238-dim bottleneck and decode back to 1265. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1031\nComponents:\n - input (input) params={\"shape\":[1,1265]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1265]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1265,\"outFeatures\":242}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":242,\"outFeatures\":238}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":238,\"outFeatures\":242}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":242,\"outFeatures\":1265}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x32x32 image with 12 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1032\nComponents:\n - input (input) params={\"shape\":[1,3,32,32]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,32,32]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":32,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":32,\"outChannels\":42,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":42,\"outChannels\":63,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":63,\"outChannels\":46,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":46,\"outFeatures\":12}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 233-token sequences with 45 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1033\nComponents:\n - input (input) params={\"shape\":[1,233]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,233]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":24573,\"embeddingDim\":96}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":96,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":96,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":96,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":96,\"outFeatures\":45}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 326-token sequences with 5 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1034\nComponents:\n - input (input) params={\"shape\":[1,326]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,326]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":23081,\"embeddingDim\":400}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":400,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[400]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":400,\"outFeatures\":5}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 2397-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1036\nComponents:\n - input (input) params={\"shape\":[1,208]}\n - fc1 (linear) params={\"inFeatures\":208,\"outFeatures\":2397}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2397,\"outFeatures\":2397}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2397,\"outFeatures\":2397}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":2397,\"outFeatures\":13}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":208,\"outFeatures\":265}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":265,\"outFeatures\":265}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":265,\"outFeatures\":265}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":265,\"outFeatures\":13}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 208-feature, 11-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1037\nComponents:\n - input (input) params={\"shape\":[1,208]}\n - fc1 (linear) params={\"inFeatures\":208,\"outFeatures\":241}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":241,\"outFeatures\":423}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":423,\"outFeatures\":177}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":177,\"outFeatures\":11}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":241}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":423}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":177}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 256-feature user input and a 96-feature item input, each through its own 2-layer MLP tower ending at width 298, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1038\nComponents:\n - user_input (input) params={\"shape\":[1,256]}\n - item_input (input) params={\"shape\":[1,96]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,256]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,96]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":256,\"outFeatures\":298}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":298,\"outFeatures\":298}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":96,\"outFeatures\":298}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":298,\"outFeatures\":298}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":596,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (89-feature input, 17 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1039\nComponents:\n - input (input) params={\"shape\":[1,89]}\n - fc1 (linear) params={\"inFeatures\":89,\"outFeatures\":8}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":8,\"outFeatures\":8}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":8,\"outFeatures\":17}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":89,\"outFeatures\":1235}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1235,\"outFeatures\":1235}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1235,\"outFeatures\":17}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 167-feature input with 62 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1040\nComponents:\n - input (input) params={\"shape\":[1,167]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,167]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":167,\"outFeatures\":262}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":262,\"outFeatures\":341}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":341,\"outFeatures\":62}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1791-dim input: encode down to a 204-dim bottleneck and decode back to 1791. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1041\nComponents:\n - input (input) params={\"shape\":[1,1791]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1791]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1791,\"outFeatures\":456}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":456,\"outFeatures\":204}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":204,\"outFeatures\":456}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":456,\"outFeatures\":1791}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x47x47 image with 5 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1042\nComponents:\n - input (input) params={\"shape\":[1,3,47,47]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,47,47]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":50,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":50,\"outChannels\":32,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":32,\"outChannels\":24,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":24,\"outFeatures\":5}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 263-token sequences with 47 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1043\nComponents:\n - input (input) params={\"shape\":[1,263]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,263]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":37552,\"embeddingDim\":116}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":116,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":116,\"outFeatures\":47}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 113-token sequences with 97 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1044\nComponents:\n - input (input) params={\"shape\":[1,113]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,113]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":49630,\"embeddingDim\":280}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":280,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[280]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":280,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[280]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":280,\"outFeatures\":97}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 2184-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1046\nComponents:\n - input (input) params={\"shape\":[1,199]}\n - fc1 (linear) params={\"inFeatures\":199,\"outFeatures\":2184}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2184,\"outFeatures\":2184}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2184,\"outFeatures\":2184}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":2184,\"outFeatures\":2184}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":2184,\"outFeatures\":7}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":199,\"outFeatures\":301}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":301,\"outFeatures\":301}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":301,\"outFeatures\":301}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":301,\"outFeatures\":301}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":301,\"outFeatures\":7}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 41-feature, 3-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1047\nComponents:\n - input (input) params={\"shape\":[1,41]}\n - fc1 (linear) params={\"inFeatures\":41,\"outFeatures\":305}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":305,\"outFeatures\":40}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":40,\"outFeatures\":3}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":305}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":40}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 246-feature user input and a 229-feature item input, each through its own 2-layer MLP tower ending at width 186, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1048\nComponents:\n - user_input (input) params={\"shape\":[1,246]}\n - item_input (input) params={\"shape\":[1,229]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,246]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,229]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":246,\"outFeatures\":186}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":186,\"outFeatures\":186}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":229,\"outFeatures\":186}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":186,\"outFeatures\":186}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":372,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (62-feature input, 46 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1049\nComponents:\n - input (input) params={\"shape\":[1,62]}\n - fc1 (linear) params={\"inFeatures\":62,\"outFeatures\":10}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":10,\"outFeatures\":10}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":10,\"outFeatures\":46}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":62,\"outFeatures\":1035}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1035,\"outFeatures\":1035}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1035,\"outFeatures\":46}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 409-feature input with 5 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1050\nComponents:\n - input (input) params={\"shape\":[1,409]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,409]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":409,\"outFeatures\":203}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":203,\"outFeatures\":154}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":154,\"outFeatures\":439}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":439,\"outFeatures\":171}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":171,\"outFeatures\":5}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1878-dim input: encode down to a 201-dim bottleneck and decode back to 1878. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1051\nComponents:\n - input (input) params={\"shape\":[1,1878]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1878]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1878,\"outFeatures\":970}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":970,\"outFeatures\":201}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":201,\"outFeatures\":970}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":970,\"outFeatures\":1878}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x39x39 image with 36 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1052\nComponents:\n - input (input) params={\"shape\":[1,3,39,39]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,39,39]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":43,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":43,\"outChannels\":8,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":8,\"outFeatures\":36}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 211-token sequences with 60 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1053\nComponents:\n - input (input) params={\"shape\":[1,211]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,211]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":9639,\"embeddingDim\":368}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":368,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":368,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":368,\"outFeatures\":60}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 489-token sequences with 51 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1054\nComponents:\n - input (input) params={\"shape\":[1,489]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,489]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":23039,\"embeddingDim\":624}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":624,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[624]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":624,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[624]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":624,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[624]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":624,\"outFeatures\":51}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (378) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-1055\nComponents:\n - input (input) params={\"shape\":[1,392]}\n - embed (embedding) params={\"numEmbeddings\":38091,\"embeddingDim\":378}\n - attn (multiHeadAttention) params={\"embedDim\":378,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":378,\"outFeatures\":44}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 3884-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1056\nComponents:\n - input (input) params={\"shape\":[1,95]}\n - fc1 (linear) params={\"inFeatures\":95,\"outFeatures\":3884}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3884,\"outFeatures\":3884}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3884,\"outFeatures\":3884}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":3884,\"outFeatures\":3}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":95,\"outFeatures\":295}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":295,\"outFeatures\":295}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":295,\"outFeatures\":295}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":295,\"outFeatures\":3}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 141-feature, 72-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1057\nComponents:\n - input (input) params={\"shape\":[1,141]}\n - fc1 (linear) params={\"inFeatures\":141,\"outFeatures\":313}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":313,\"outFeatures\":188}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":188,\"outFeatures\":212}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":212,\"outFeatures\":87}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":87,\"outFeatures\":377}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":377,\"outFeatures\":72}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":313}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":188}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":212}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":87}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":377}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 240-feature user input and a 155-feature item input, each through its own 2-layer MLP tower ending at width 334, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1058\nComponents:\n - user_input (input) params={\"shape\":[1,240]}\n - item_input (input) params={\"shape\":[1,155]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,240]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,155]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":240,\"outFeatures\":334}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":334,\"outFeatures\":334}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":155,\"outFeatures\":334}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":334,\"outFeatures\":334}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":668,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (68-feature input, 46 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1059\nComponents:\n - input (input) params={\"shape\":[1,68]}\n - fc1 (linear) params={\"inFeatures\":68,\"outFeatures\":5}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":5,\"outFeatures\":5}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":5,\"outFeatures\":46}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":68,\"outFeatures\":656}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":656,\"outFeatures\":656}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":656,\"outFeatures\":46}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 152-feature input with 63 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1060\nComponents:\n - input (input) params={\"shape\":[1,152]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,152]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":152,\"outFeatures\":453}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":453,\"outFeatures\":594}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":594,\"outFeatures\":468}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":468,\"outFeatures\":617}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":617,\"outFeatures\":493}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":493,\"outFeatures\":63}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1780-dim input: encode down to a 129-dim bottleneck and decode back to 1780. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1061\nComponents:\n - input (input) params={\"shape\":[1,1780]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1780]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1780,\"outFeatures\":572}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":572,\"outFeatures\":129}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":129,\"outFeatures\":572}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":572,\"outFeatures\":1780}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x38x38 image with 51 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1062\nComponents:\n - input (input) params={\"shape\":[1,3,38,38]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,38,38]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":23,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":23,\"outChannels\":27,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":27,\"outFeatures\":51}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 242-token sequences with 82 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1063\nComponents:\n - input (input) params={\"shape\":[1,242]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,242]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":30021,\"embeddingDim\":64}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":64,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":64,\"outFeatures\":82}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 450-token sequences with 75 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1064\nComponents:\n - input (input) params={\"shape\":[1,450]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,450]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":37081,\"embeddingDim\":400}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":400,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[400]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":400,\"outFeatures\":75}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (486) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-1065\nComponents:\n - input (input) params={\"shape\":[1,327]}\n - embed (embedding) params={\"numEmbeddings\":37338,\"embeddingDim\":486}\n - attn (multiHeadAttention) params={\"embedDim\":486,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":486,\"outFeatures\":81}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 3191-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1066\nComponents:\n - input (input) params={\"shape\":[1,159]}\n - fc1 (linear) params={\"inFeatures\":159,\"outFeatures\":3191}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3191,\"outFeatures\":3191}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":3191,\"outFeatures\":35}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":159,\"outFeatures\":103}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":103,\"outFeatures\":103}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":103,\"outFeatures\":35}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 135-feature, 17-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1067\nComponents:\n - input (input) params={\"shape\":[1,135]}\n - fc1 (linear) params={\"inFeatures\":135,\"outFeatures\":251}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":251,\"outFeatures\":168}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":168,\"outFeatures\":313}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":313,\"outFeatures\":148}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":148,\"outFeatures\":220}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":220,\"outFeatures\":17}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":251}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":168}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":313}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":148}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":220}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 101-feature user input and a 29-feature item input, each through its own 2-layer MLP tower ending at width 465, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1068\nComponents:\n - user_input (input) params={\"shape\":[1,101]}\n - item_input (input) params={\"shape\":[1,29]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,101]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,29]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":101,\"outFeatures\":465}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":465,\"outFeatures\":465}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":29,\"outFeatures\":465}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":465,\"outFeatures\":465}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":930,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (67-feature input, 5 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1069\nComponents:\n - input (input) params={\"shape\":[1,67]}\n - fc1 (linear) params={\"inFeatures\":67,\"outFeatures\":12}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":12,\"outFeatures\":12}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":12,\"outFeatures\":5}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":67,\"outFeatures\":790}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":790,\"outFeatures\":790}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":790,\"outFeatures\":5}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 325-feature input with 191 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1070\nComponents:\n - input (input) params={\"shape\":[1,325]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,325]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":325,\"outFeatures\":618}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":618,\"outFeatures\":341}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":341,\"outFeatures\":505}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":505,\"outFeatures\":759}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":759,\"outFeatures\":989}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":989,\"outFeatures\":191}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1846-dim input: encode down to a 19-dim bottleneck and decode back to 1846. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1071\nComponents:\n - input (input) params={\"shape\":[1,1846]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1846]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1846,\"outFeatures\":773}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":773,\"outFeatures\":19}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":19,\"outFeatures\":773}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":773,\"outFeatures\":1846}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x42x42 image with 93 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1072\nComponents:\n - input (input) params={\"shape\":[1,3,42,42]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,42,42]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":16,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":16,\"outChannels\":47,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":47,\"outChannels\":20,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":20,\"outFeatures\":93}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 166-token sequences with 24 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1073\nComponents:\n - input (input) params={\"shape\":[1,166]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,166]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":20225,\"embeddingDim\":112}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":112,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":112,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":112,\"outFeatures\":24}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 260-token sequences with 3 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1074\nComponents:\n - input (input) params={\"shape\":[1,260]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,260]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":33901,\"embeddingDim\":736}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":736,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[736]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":736,\"outFeatures\":3}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 3398-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1076\nComponents:\n - input (input) params={\"shape\":[1,227]}\n - fc1 (linear) params={\"inFeatures\":227,\"outFeatures\":3398}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3398,\"outFeatures\":3398}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3398,\"outFeatures\":3398}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":3398,\"outFeatures\":35}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":227,\"outFeatures\":258}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":258,\"outFeatures\":258}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":258,\"outFeatures\":258}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":258,\"outFeatures\":35}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 19-feature, 30-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1077\nComponents:\n - input (input) params={\"shape\":[1,19]}\n - fc1 (linear) params={\"inFeatures\":19,\"outFeatures\":487}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":487,\"outFeatures\":413}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":413,\"outFeatures\":75}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":75,\"outFeatures\":253}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":253,\"outFeatures\":30}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":487}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":413}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":75}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":253}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 201-feature user input and a 24-feature item input, each through its own 2-layer MLP tower ending at width 107, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1078\nComponents:\n - user_input (input) params={\"shape\":[1,201]}\n - item_input (input) params={\"shape\":[1,24]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,201]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,24]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":201,\"outFeatures\":107}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":107,\"outFeatures\":107}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":24,\"outFeatures\":107}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":107,\"outFeatures\":107}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":214,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (22-feature input, 46 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1079\nComponents:\n - input (input) params={\"shape\":[1,22]}\n - fc1 (linear) params={\"inFeatures\":22,\"outFeatures\":6}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":6,\"outFeatures\":6}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":6,\"outFeatures\":46}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":22,\"outFeatures\":1400}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1400,\"outFeatures\":1400}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1400,\"outFeatures\":46}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 17-feature input with 69 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1080\nComponents:\n - input (input) params={\"shape\":[1,17]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,17]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":17,\"outFeatures\":993}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":993,\"outFeatures\":601}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":601,\"outFeatures\":643}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":643,\"outFeatures\":999}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":999,\"outFeatures\":69}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1444-dim input: encode down to a 147-dim bottleneck and decode back to 1444. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1081\nComponents:\n - input (input) params={\"shape\":[1,1444]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1444]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1444,\"outFeatures\":1021}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":1021,\"outFeatures\":147}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":147,\"outFeatures\":1021}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":1021,\"outFeatures\":1444}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x45x45 image with 86 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1082\nComponents:\n - input (input) params={\"shape\":[1,3,45,45]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,45,45]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":24,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":24,\"outChannels\":48,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":48,\"outChannels\":39,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":39,\"outChannels\":26,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":26,\"outFeatures\":86}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 219-token sequences with 54 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1083\nComponents:\n - input (input) params={\"shape\":[1,219]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,219]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":36607,\"embeddingDim\":80}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":80,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":80,\"outFeatures\":54}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 463-token sequences with 69 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1084\nComponents:\n - input (input) params={\"shape\":[1,463]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,463]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":21209,\"embeddingDim\":352}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":352,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[352]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":352,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[352]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":352,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[352]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":352,\"outFeatures\":69}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3370-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1086\nComponents:\n - input (input) params={\"shape\":[1,226]}\n - fc1 (linear) params={\"inFeatures\":226,\"outFeatures\":3370}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3370,\"outFeatures\":3370}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3370,\"outFeatures\":3370}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3370,\"outFeatures\":3370}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3370,\"outFeatures\":47}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":226,\"outFeatures\":284}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":284,\"outFeatures\":284}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":284,\"outFeatures\":284}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":284,\"outFeatures\":284}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":284,\"outFeatures\":47}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 129-feature, 49-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1087\nComponents:\n - input (input) params={\"shape\":[1,129]}\n - fc1 (linear) params={\"inFeatures\":129,\"outFeatures\":44}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":44,\"outFeatures\":136}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":136,\"outFeatures\":448}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":448,\"outFeatures\":49}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":44}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":136}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":448}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 222-feature user input and a 172-feature item input, each through its own 2-layer MLP tower ending at width 365, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1088\nComponents:\n - user_input (input) params={\"shape\":[1,222]}\n - item_input (input) params={\"shape\":[1,172]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,222]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,172]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":222,\"outFeatures\":365}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":365,\"outFeatures\":365}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":172,\"outFeatures\":365}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":365,\"outFeatures\":365}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":730,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (16-feature input, 4 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1089\nComponents:\n - input (input) params={\"shape\":[1,16]}\n - fc1 (linear) params={\"inFeatures\":16,\"outFeatures\":7}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":7,\"outFeatures\":7}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":7,\"outFeatures\":4}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":16,\"outFeatures\":1176}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1176,\"outFeatures\":1176}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1176,\"outFeatures\":4}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 182-feature input with 120 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1090\nComponents:\n - input (input) params={\"shape\":[1,182]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,182]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":182,\"outFeatures\":889}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":889,\"outFeatures\":213}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":213,\"outFeatures\":77}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":77,\"outFeatures\":642}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":642,\"outFeatures\":609}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":609,\"outFeatures\":460}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":460,\"outFeatures\":120}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1792-dim input: encode down to a 225-dim bottleneck and decode back to 1792. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1091\nComponents:\n - input (input) params={\"shape\":[1,1792]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1792]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1792,\"outFeatures\":295}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":295,\"outFeatures\":225}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":225,\"outFeatures\":295}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":295,\"outFeatures\":1792}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x42x42 image with 46 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1092\nComponents:\n - input (input) params={\"shape\":[1,3,42,42]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,42,42]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":60,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":60,\"outChannels\":36,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":36,\"outChannels\":48,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":48,\"outChannels\":33,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":33,\"outFeatures\":46}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 478-token sequences with 30 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1093\nComponents:\n - input (input) params={\"shape\":[1,478]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,478]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":19874,\"embeddingDim\":92}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":92,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":92,\"outFeatures\":30}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 409-token sequences with 64 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1094\nComponents:\n - input (input) params={\"shape\":[1,409]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,409]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":39083,\"embeddingDim\":144}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":144,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[144]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":144,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[144]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":144,\"outFeatures\":64}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 3136-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1096\nComponents:\n - input (input) params={\"shape\":[1,251]}\n - fc1 (linear) params={\"inFeatures\":251,\"outFeatures\":3136}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3136,\"outFeatures\":3136}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":3136,\"outFeatures\":23}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":251,\"outFeatures\":179}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":179,\"outFeatures\":179}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":179,\"outFeatures\":23}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 159-feature, 40-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1097\nComponents:\n - input (input) params={\"shape\":[1,159]}\n - fc1 (linear) params={\"inFeatures\":159,\"outFeatures\":90}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":90,\"outFeatures\":84}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":84,\"outFeatures\":238}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":238,\"outFeatures\":162}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":162,\"outFeatures\":40}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":90}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":84}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":238}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":162}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 27-feature user input and a 137-feature item input, each through its own 2-layer MLP tower ending at width 502, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1098\nComponents:\n - user_input (input) params={\"shape\":[1,27]}\n - item_input (input) params={\"shape\":[1,137]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,27]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,137]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":27,\"outFeatures\":502}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":502,\"outFeatures\":502}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":137,\"outFeatures\":502}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":502,\"outFeatures\":502}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":1004,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (39-feature input, 29 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1099\nComponents:\n - input (input) params={\"shape\":[1,39]}\n - fc1 (linear) params={\"inFeatures\":39,\"outFeatures\":5}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":5,\"outFeatures\":5}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":5,\"outFeatures\":29}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":39,\"outFeatures\":869}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":869,\"outFeatures\":869}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":869,\"outFeatures\":29}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 371-feature input with 196 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1100\nComponents:\n - input (input) params={\"shape\":[1,371]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,371]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":371,\"outFeatures\":861}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":861,\"outFeatures\":729}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":729,\"outFeatures\":634}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":634,\"outFeatures\":928}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":928,\"outFeatures\":670}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":670,\"outFeatures\":767}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":767,\"outFeatures\":196}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1454-dim input: encode down to a 44-dim bottleneck and decode back to 1454. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1101\nComponents:\n - input (input) params={\"shape\":[1,1454]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1454]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1454,\"outFeatures\":708}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":708,\"outFeatures\":44}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":44,\"outFeatures\":708}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":708,\"outFeatures\":1454}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x46x46 image with 97 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1102\nComponents:\n - input (input) params={\"shape\":[1,3,46,46]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,46,46]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":28,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":28,\"outChannels\":48,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":48,\"outChannels\":57,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":57,\"outChannels\":40,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":40,\"outFeatures\":97}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 49-token sequences with 30 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1103\nComponents:\n - input (input) params={\"shape\":[1,49]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,49]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":46962,\"embeddingDim\":200}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":200,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":200,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":200,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":200,\"outFeatures\":30}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 293-token sequences with 71 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1104\nComponents:\n - input (input) params={\"shape\":[1,293]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,293]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":30555,\"embeddingDim\":528}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":528,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[528]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":528,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[528]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":528,\"outFeatures\":71}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (120) is not divisible by numHeads (7). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-1105\nComponents:\n - input (input) params={\"shape\":[1,239]}\n - embed (embedding) params={\"numEmbeddings\":15382,\"embeddingDim\":120}\n - attn (multiHeadAttention) params={\"embedDim\":120,\"numHeads\":7}\n - head (linear) params={\"inFeatures\":120,\"outFeatures\":38}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":8}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3770-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1106\nComponents:\n - input (input) params={\"shape\":[1,164]}\n - fc1 (linear) params={\"inFeatures\":164,\"outFeatures\":3770}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3770,\"outFeatures\":3770}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3770,\"outFeatures\":3770}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3770,\"outFeatures\":3770}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3770,\"outFeatures\":30}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":164,\"outFeatures\":344}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":344,\"outFeatures\":344}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":344,\"outFeatures\":344}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":344,\"outFeatures\":344}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":344,\"outFeatures\":30}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 114-feature, 44-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1107\nComponents:\n - input (input) params={\"shape\":[1,114]}\n - fc1 (linear) params={\"inFeatures\":114,\"outFeatures\":486}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":486,\"outFeatures\":486}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":486,\"outFeatures\":289}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":289,\"outFeatures\":259}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":259,\"outFeatures\":67}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":67,\"outFeatures\":44}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":486}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":486}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":289}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":259}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":67}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 215-feature user input and a 112-feature item input, each through its own 2-layer MLP tower ending at width 275, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1108\nComponents:\n - user_input (input) params={\"shape\":[1,215]}\n - item_input (input) params={\"shape\":[1,112]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,215]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,112]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":215,\"outFeatures\":275}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":275,\"outFeatures\":275}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":112,\"outFeatures\":275}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":275,\"outFeatures\":275}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":550,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (93-feature input, 7 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1109\nComponents:\n - input (input) params={\"shape\":[1,93]}\n - fc1 (linear) params={\"inFeatures\":93,\"outFeatures\":4}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":4,\"outFeatures\":4}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":4,\"outFeatures\":7}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":93,\"outFeatures\":1387}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1387,\"outFeatures\":1387}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1387,\"outFeatures\":7}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 277-feature input with 50 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1110\nComponents:\n - input (input) params={\"shape\":[1,277]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,277]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":277,\"outFeatures\":186}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":186,\"outFeatures\":571}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":571,\"outFeatures\":695}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":695,\"outFeatures\":595}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":595,\"outFeatures\":50}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1300-dim input: encode down to a 125-dim bottleneck and decode back to 1300. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1111\nComponents:\n - input (input) params={\"shape\":[1,1300]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1300]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1300,\"outFeatures\":514}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":514,\"outFeatures\":125}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":125,\"outFeatures\":514}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":514,\"outFeatures\":1300}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x49x49 image with 89 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1112\nComponents:\n - input (input) params={\"shape\":[1,3,49,49]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,49,49]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":39,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":39,\"outChannels\":10,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":10,\"outChannels\":37,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":37,\"outFeatures\":89}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 90-token sequences with 2 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1113\nComponents:\n - input (input) params={\"shape\":[1,90]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,90]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":27220,\"embeddingDim\":512}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":512,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":512,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":512,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":512,\"outFeatures\":2}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 443-token sequences with 5 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1114\nComponents:\n - input (input) params={\"shape\":[1,443]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,443]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":19046,\"embeddingDim\":352}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":352,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[352]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":352,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[352]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":352,\"outFeatures\":5}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3685-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1116\nComponents:\n - input (input) params={\"shape\":[1,57]}\n - fc1 (linear) params={\"inFeatures\":57,\"outFeatures\":3685}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3685,\"outFeatures\":3685}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3685,\"outFeatures\":3685}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3685,\"outFeatures\":3685}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3685,\"outFeatures\":49}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":57,\"outFeatures\":73}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":73,\"outFeatures\":73}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":73,\"outFeatures\":73}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":73,\"outFeatures\":73}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":73,\"outFeatures\":49}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 238-feature, 7-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1117\nComponents:\n - input (input) params={\"shape\":[1,238]}\n - fc1 (linear) params={\"inFeatures\":238,\"outFeatures\":45}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":45,\"outFeatures\":93}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":93,\"outFeatures\":400}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":400,\"outFeatures\":7}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":45}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":93}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":400}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 84-feature user input and a 56-feature item input, each through its own 2-layer MLP tower ending at width 209, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1118\nComponents:\n - user_input (input) params={\"shape\":[1,84]}\n - item_input (input) params={\"shape\":[1,56]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,84]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,56]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":84,\"outFeatures\":209}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":209,\"outFeatures\":209}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":56,\"outFeatures\":209}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":209,\"outFeatures\":209}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":418,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (62-feature input, 4 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1119\nComponents:\n - input (input) params={\"shape\":[1,62]}\n - fc1 (linear) params={\"inFeatures\":62,\"outFeatures\":19}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":19,\"outFeatures\":19}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":19,\"outFeatures\":4}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":62,\"outFeatures\":1378}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1378,\"outFeatures\":1378}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1378,\"outFeatures\":4}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 298-feature input with 31 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1120\nComponents:\n - input (input) params={\"shape\":[1,298]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,298]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":298,\"outFeatures\":385}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":385,\"outFeatures\":889}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":889,\"outFeatures\":31}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 800-dim input: encode down to a 87-dim bottleneck and decode back to 800. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1121\nComponents:\n - input (input) params={\"shape\":[1,800]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,800]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":800,\"outFeatures\":306}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":306,\"outFeatures\":87}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":87,\"outFeatures\":306}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":306,\"outFeatures\":800}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x37x37 image with 88 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1122\nComponents:\n - input (input) params={\"shape\":[1,3,37,37]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,37,37]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":54,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":54,\"outChannels\":28,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":28,\"outFeatures\":88}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 227-token sequences with 96 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1123\nComponents:\n - input (input) params={\"shape\":[1,227]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,227]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":46289,\"embeddingDim\":88}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":88,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":88,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":88,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":88,\"outFeatures\":96}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 441-token sequences with 96 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1124\nComponents:\n - input (input) params={\"shape\":[1,441]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,441]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":28311,\"embeddingDim\":256}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":256,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[256]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":256,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[256]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":256,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[256]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":256,\"outFeatures\":96}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3255-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1126\nComponents:\n - input (input) params={\"shape\":[1,33]}\n - fc1 (linear) params={\"inFeatures\":33,\"outFeatures\":3255}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3255,\"outFeatures\":3255}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3255,\"outFeatures\":3255}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3255,\"outFeatures\":3255}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3255,\"outFeatures\":46}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":33,\"outFeatures\":310}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":310,\"outFeatures\":310}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":310,\"outFeatures\":310}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":310,\"outFeatures\":310}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":310,\"outFeatures\":46}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 64-feature, 47-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1127\nComponents:\n - input (input) params={\"shape\":[1,64]}\n - fc1 (linear) params={\"inFeatures\":64,\"outFeatures\":226}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":226,\"outFeatures\":156}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":156,\"outFeatures\":342}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":342,\"outFeatures\":47}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":226}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":156}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":342}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 178-feature user input and a 121-feature item input, each through its own 2-layer MLP tower ending at width 241, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1128\nComponents:\n - user_input (input) params={\"shape\":[1,178]}\n - item_input (input) params={\"shape\":[1,121]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,178]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,121]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":178,\"outFeatures\":241}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":241,\"outFeatures\":241}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":121,\"outFeatures\":241}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":241,\"outFeatures\":241}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":482,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (116-feature input, 36 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1129\nComponents:\n - input (input) params={\"shape\":[1,116]}\n - fc1 (linear) params={\"inFeatures\":116,\"outFeatures\":11}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":11,\"outFeatures\":11}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":11,\"outFeatures\":36}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":116,\"outFeatures\":771}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":771,\"outFeatures\":771}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":771,\"outFeatures\":36}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 361-feature input with 13 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1130\nComponents:\n - input (input) params={\"shape\":[1,361]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,361]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":361,\"outFeatures\":734}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":734,\"outFeatures\":976}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":976,\"outFeatures\":629}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":629,\"outFeatures\":13}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1474-dim input: encode down to a 42-dim bottleneck and decode back to 1474. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1131\nComponents:\n - input (input) params={\"shape\":[1,1474]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1474]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1474,\"outFeatures\":278}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":278,\"outFeatures\":42}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":42,\"outFeatures\":278}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":278,\"outFeatures\":1474}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x30x30 image with 82 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1132\nComponents:\n - input (input) params={\"shape\":[1,3,30,30]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,30,30]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":35,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":35,\"outChannels\":9,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":9,\"outFeatures\":82}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 501-token sequences with 67 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1133\nComponents:\n - input (input) params={\"shape\":[1,501]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,501]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":46675,\"embeddingDim\":72}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":72,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":72,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":72,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":72,\"outFeatures\":67}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 315-token sequences with 87 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1134\nComponents:\n - input (input) params={\"shape\":[1,315]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,315]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":26213,\"embeddingDim\":320}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":320,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[320]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":320,\"outFeatures\":87}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 3364-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1136\nComponents:\n - input (input) params={\"shape\":[1,187]}\n - fc1 (linear) params={\"inFeatures\":187,\"outFeatures\":3364}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3364,\"outFeatures\":3364}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3364,\"outFeatures\":3364}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":3364,\"outFeatures\":15}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":187,\"outFeatures\":214}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":214,\"outFeatures\":214}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":214,\"outFeatures\":214}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":214,\"outFeatures\":15}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 206-feature, 54-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1137\nComponents:\n - input (input) params={\"shape\":[1,206]}\n - fc1 (linear) params={\"inFeatures\":206,\"outFeatures\":145}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":145,\"outFeatures\":152}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":152,\"outFeatures\":439}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":439,\"outFeatures\":312}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":312,\"outFeatures\":437}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":437,\"outFeatures\":54}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":145}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":152}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":439}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":312}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":437}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 17-feature user input and a 75-feature item input, each through its own 2-layer MLP tower ending at width 52, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1138\nComponents:\n - user_input (input) params={\"shape\":[1,17]}\n - item_input (input) params={\"shape\":[1,75]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,17]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,75]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":17,\"outFeatures\":52}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":52,\"outFeatures\":52}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":75,\"outFeatures\":52}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":52,\"outFeatures\":52}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":104,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (47-feature input, 28 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1139\nComponents:\n - input (input) params={\"shape\":[1,47]}\n - fc1 (linear) params={\"inFeatures\":47,\"outFeatures\":14}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":14,\"outFeatures\":14}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":14,\"outFeatures\":28}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":47,\"outFeatures\":641}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":641,\"outFeatures\":641}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":641,\"outFeatures\":28}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 114-feature input with 112 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1140\nComponents:\n - input (input) params={\"shape\":[1,114]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,114]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":114,\"outFeatures\":969}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":969,\"outFeatures\":603}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":603,\"outFeatures\":215}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":215,\"outFeatures\":112}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 643-dim input: encode down to a 117-dim bottleneck and decode back to 643. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1141\nComponents:\n - input (input) params={\"shape\":[1,643]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,643]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":643,\"outFeatures\":635}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":635,\"outFeatures\":117}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":117,\"outFeatures\":635}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":635,\"outFeatures\":643}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x32x32 image with 83 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1142\nComponents:\n - input (input) params={\"shape\":[1,3,32,32]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,32,32]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":31,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":31,\"outChannels\":61,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":61,\"outChannels\":63,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":63,\"outChannels\":46,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":46,\"outFeatures\":83}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 78-token sequences with 39 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1143\nComponents:\n - input (input) params={\"shape\":[1,78]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,78]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":45382,\"embeddingDim\":68}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":68,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":68,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":68,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":68,\"outFeatures\":39}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 315-token sequences with 89 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1144\nComponents:\n - input (input) params={\"shape\":[1,315]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,315]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":47744,\"embeddingDim\":152}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":152,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[152]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":152,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[152]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":152,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[152]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":152,\"outFeatures\":89}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 2132-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1146\nComponents:\n - input (input) params={\"shape\":[1,100]}\n - fc1 (linear) params={\"inFeatures\":100,\"outFeatures\":2132}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2132,\"outFeatures\":2132}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":2132,\"outFeatures\":38}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":100,\"outFeatures\":123}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":123,\"outFeatures\":123}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":123,\"outFeatures\":38}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 252-feature, 41-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1147\nComponents:\n - input (input) params={\"shape\":[1,252]}\n - fc1 (linear) params={\"inFeatures\":252,\"outFeatures\":120}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":120,\"outFeatures\":182}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":182,\"outFeatures\":231}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":231,\"outFeatures\":41}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":120}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":182}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":231}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 175-feature user input and a 38-feature item input, each through its own 2-layer MLP tower ending at width 325, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1148\nComponents:\n - user_input (input) params={\"shape\":[1,175]}\n - item_input (input) params={\"shape\":[1,38]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,175]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,38]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":175,\"outFeatures\":325}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":325,\"outFeatures\":325}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":38,\"outFeatures\":325}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":325,\"outFeatures\":325}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":650,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (77-feature input, 38 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1149\nComponents:\n - input (input) params={\"shape\":[1,77]}\n - fc1 (linear) params={\"inFeatures\":77,\"outFeatures\":24}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":24,\"outFeatures\":24}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":24,\"outFeatures\":38}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":77,\"outFeatures\":684}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":684,\"outFeatures\":684}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":684,\"outFeatures\":38}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 71-feature input with 91 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1150\nComponents:\n - input (input) params={\"shape\":[1,71]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,71]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":71,\"outFeatures\":199}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":199,\"outFeatures\":520}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":520,\"outFeatures\":272}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":272,\"outFeatures\":91}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1537-dim input: encode down to a 43-dim bottleneck and decode back to 1537. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1151\nComponents:\n - input (input) params={\"shape\":[1,1537]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1537]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1537,\"outFeatures\":887}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":887,\"outFeatures\":43}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":43,\"outFeatures\":887}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":887,\"outFeatures\":1537}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x29x29 image with 3 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1152\nComponents:\n - input (input) params={\"shape\":[1,3,29,29]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,29,29]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":50,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":50,\"outChannels\":46,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":46,\"outChannels\":50,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":50,\"outChannels\":40,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":40,\"outFeatures\":3}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 80-token sequences with 54 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1153\nComponents:\n - input (input) params={\"shape\":[1,80]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,80]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":24000,\"embeddingDim\":104}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":104,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":104,\"outFeatures\":54}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 414-token sequences with 51 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1154\nComponents:\n - input (input) params={\"shape\":[1,414]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,414]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":12900,\"embeddingDim\":320}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":320,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[320]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":320,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[320]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":320,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[320]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":320,\"outFeatures\":51}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (426) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-1155\nComponents:\n - input (input) params={\"shape\":[1,67]}\n - embed (embedding) params={\"numEmbeddings\":42997,\"embeddingDim\":426}\n - attn (multiHeadAttention) params={\"embedDim\":426,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":426,\"outFeatures\":25}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 2266-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1156\nComponents:\n - input (input) params={\"shape\":[1,240]}\n - fc1 (linear) params={\"inFeatures\":240,\"outFeatures\":2266}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2266,\"outFeatures\":2266}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2266,\"outFeatures\":2266}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":2266,\"outFeatures\":2266}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":2266,\"outFeatures\":47}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":240,\"outFeatures\":191}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":191,\"outFeatures\":191}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":191,\"outFeatures\":191}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":191,\"outFeatures\":191}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":191,\"outFeatures\":47}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 117-feature, 58-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1157\nComponents:\n - input (input) params={\"shape\":[1,117]}\n - fc1 (linear) params={\"inFeatures\":117,\"outFeatures\":364}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":364,\"outFeatures\":298}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":298,\"outFeatures\":58}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":364}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":298}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 67-feature user input and a 80-feature item input, each through its own 2-layer MLP tower ending at width 377, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1158\nComponents:\n - user_input (input) params={\"shape\":[1,67]}\n - item_input (input) params={\"shape\":[1,80]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,67]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,80]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":67,\"outFeatures\":377}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":377,\"outFeatures\":377}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":80,\"outFeatures\":377}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":377,\"outFeatures\":377}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":754,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (73-feature input, 5 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1159\nComponents:\n - input (input) params={\"shape\":[1,73]}\n - fc1 (linear) params={\"inFeatures\":73,\"outFeatures\":10}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":10,\"outFeatures\":10}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":10,\"outFeatures\":5}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":73,\"outFeatures\":1227}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1227,\"outFeatures\":1227}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1227,\"outFeatures\":5}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 470-feature input with 122 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1160\nComponents:\n - input (input) params={\"shape\":[1,470]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,470]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":470,\"outFeatures\":212}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":212,\"outFeatures\":22}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":22,\"outFeatures\":135}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":135,\"outFeatures\":754}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":754,\"outFeatures\":636}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":636,\"outFeatures\":122}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1886-dim input: encode down to a 75-dim bottleneck and decode back to 1886. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1161\nComponents:\n - input (input) params={\"shape\":[1,1886]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1886]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1886,\"outFeatures\":851}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":851,\"outFeatures\":75}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":75,\"outFeatures\":851}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":851,\"outFeatures\":1886}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x24x24 image with 37 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1162\nComponents:\n - input (input) params={\"shape\":[1,3,24,24]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,24,24]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":30,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":30,\"outChannels\":54,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":54,\"outFeatures\":37}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 34-token sequences with 2 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1163\nComponents:\n - input (input) params={\"shape\":[1,34]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,34]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":46559,\"embeddingDim\":56}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":56,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":56,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":56,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":56,\"outFeatures\":2}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 212-token sequences with 22 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1164\nComponents:\n - input (input) params={\"shape\":[1,212]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,212]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":40366,\"embeddingDim\":136}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":136,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[136]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":136,\"outFeatures\":22}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 1979-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1166\nComponents:\n - input (input) params={\"shape\":[1,235]}\n - fc1 (linear) params={\"inFeatures\":235,\"outFeatures\":1979}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":1979,\"outFeatures\":1979}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":1979,\"outFeatures\":1979}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":1979,\"outFeatures\":1979}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":1979,\"outFeatures\":38}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":235,\"outFeatures\":314}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":314,\"outFeatures\":314}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":314,\"outFeatures\":314}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":314,\"outFeatures\":314}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":314,\"outFeatures\":38}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 210-feature, 45-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1167\nComponents:\n - input (input) params={\"shape\":[1,210]}\n - fc1 (linear) params={\"inFeatures\":210,\"outFeatures\":274}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":274,\"outFeatures\":464}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":464,\"outFeatures\":247}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":247,\"outFeatures\":101}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":101,\"outFeatures\":389}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":389,\"outFeatures\":45}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":274}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":464}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":247}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":101}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":389}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 93-feature user input and a 83-feature item input, each through its own 2-layer MLP tower ending at width 448, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1168\nComponents:\n - user_input (input) params={\"shape\":[1,93]}\n - item_input (input) params={\"shape\":[1,83]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,93]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,83]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":93,\"outFeatures\":448}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":448,\"outFeatures\":448}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":83,\"outFeatures\":448}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":448,\"outFeatures\":448}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":896,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (96-feature input, 42 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1169\nComponents:\n - input (input) params={\"shape\":[1,96]}\n - fc1 (linear) params={\"inFeatures\":96,\"outFeatures\":8}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":8,\"outFeatures\":8}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":8,\"outFeatures\":42}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":96,\"outFeatures\":1126}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1126,\"outFeatures\":1126}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1126,\"outFeatures\":42}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 237-feature input with 34 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1170\nComponents:\n - input (input) params={\"shape\":[1,237]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,237]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":237,\"outFeatures\":989}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":989,\"outFeatures\":620}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":620,\"outFeatures\":236}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":236,\"outFeatures\":34}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 281-dim input: encode down to a 8-dim bottleneck and decode back to 281. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1171\nComponents:\n - input (input) params={\"shape\":[1,281]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,281]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":281,\"outFeatures\":110}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":110,\"outFeatures\":8}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":8,\"outFeatures\":110}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":110,\"outFeatures\":281}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x34x34 image with 65 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1172\nComponents:\n - input (input) params={\"shape\":[1,3,34,34]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,34,34]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":19,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":19,\"outChannels\":36,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":36,\"outChannels\":43,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":43,\"outFeatures\":65}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 377-token sequences with 66 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1173\nComponents:\n - input (input) params={\"shape\":[1,377]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,377]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":35517,\"embeddingDim\":78}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":78,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":78,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":78,\"outFeatures\":66}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 457-token sequences with 40 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1174\nComponents:\n - input (input) params={\"shape\":[1,457]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,457]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":29169,\"embeddingDim\":112}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":112,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[112]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":112,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[112]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":112,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[112]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":112,\"outFeatures\":40}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3074-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1176\nComponents:\n - input (input) params={\"shape\":[1,121]}\n - fc1 (linear) params={\"inFeatures\":121,\"outFeatures\":3074}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3074,\"outFeatures\":3074}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3074,\"outFeatures\":3074}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3074,\"outFeatures\":3074}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3074,\"outFeatures\":30}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":121,\"outFeatures\":108}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":108,\"outFeatures\":108}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":108,\"outFeatures\":108}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":108,\"outFeatures\":108}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":108,\"outFeatures\":30}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 192-feature, 17-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1177\nComponents:\n - input (input) params={\"shape\":[1,192]}\n - fc1 (linear) params={\"inFeatures\":192,\"outFeatures\":418}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":418,\"outFeatures\":304}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":304,\"outFeatures\":134}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":134,\"outFeatures\":17}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":418}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":304}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":134}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 238-feature user input and a 24-feature item input, each through its own 2-layer MLP tower ending at width 296, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1178\nComponents:\n - user_input (input) params={\"shape\":[1,238]}\n - item_input (input) params={\"shape\":[1,24]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,238]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,24]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":238,\"outFeatures\":296}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":296,\"outFeatures\":296}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":24,\"outFeatures\":296}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":296,\"outFeatures\":296}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":592,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (38-feature input, 47 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1179\nComponents:\n - input (input) params={\"shape\":[1,38]}\n - fc1 (linear) params={\"inFeatures\":38,\"outFeatures\":16}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":16,\"outFeatures\":16}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":16,\"outFeatures\":47}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":38,\"outFeatures\":1126}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1126,\"outFeatures\":1126}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1126,\"outFeatures\":47}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 37-feature input with 56 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1180\nComponents:\n - input (input) params={\"shape\":[1,37]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,37]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":37,\"outFeatures\":477}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":477,\"outFeatures\":801}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":801,\"outFeatures\":334}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":334,\"outFeatures\":969}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":969,\"outFeatures\":117}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":117,\"outFeatures\":56}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 887-dim input: encode down to a 14-dim bottleneck and decode back to 887. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1181\nComponents:\n - input (input) params={\"shape\":[1,887]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,887]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":887,\"outFeatures\":693}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":693,\"outFeatures\":14}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":14,\"outFeatures\":693}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":693,\"outFeatures\":887}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x54x54 image with 84 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1182\nComponents:\n - input (input) params={\"shape\":[1,3,54,54]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,54,54]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":35,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":35,\"outChannels\":31,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":31,\"outChannels\":54,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":54,\"outFeatures\":84}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 281-token sequences with 9 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1183\nComponents:\n - input (input) params={\"shape\":[1,281]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,281]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":38350,\"embeddingDim\":104}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":104,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":104,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":104,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":104,\"outFeatures\":9}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 276-token sequences with 88 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1184\nComponents:\n - input (input) params={\"shape\":[1,276]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,276]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":26462,\"embeddingDim\":272}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":272,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[272]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":272,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[272]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":272,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[272]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":272,\"outFeatures\":88}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 2481-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1186\nComponents:\n - input (input) params={\"shape\":[1,127]}\n - fc1 (linear) params={\"inFeatures\":127,\"outFeatures\":2481}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2481,\"outFeatures\":2481}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":2481,\"outFeatures\":41}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":127,\"outFeatures\":224}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":224,\"outFeatures\":224}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":224,\"outFeatures\":41}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 256-feature, 17-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1187\nComponents:\n - input (input) params={\"shape\":[1,256]}\n - fc1 (linear) params={\"inFeatures\":256,\"outFeatures\":395}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":395,\"outFeatures\":296}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":296,\"outFeatures\":133}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":133,\"outFeatures\":359}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":359,\"outFeatures\":353}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":353,\"outFeatures\":17}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":395}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":296}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":133}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":359}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":353}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 58-feature user input and a 182-feature item input, each through its own 2-layer MLP tower ending at width 119, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1188\nComponents:\n - user_input (input) params={\"shape\":[1,58]}\n - item_input (input) params={\"shape\":[1,182]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,58]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,182]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":58,\"outFeatures\":119}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":119,\"outFeatures\":119}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":182,\"outFeatures\":119}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":119,\"outFeatures\":119}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":238,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (69-feature input, 16 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1189\nComponents:\n - input (input) params={\"shape\":[1,69]}\n - fc1 (linear) params={\"inFeatures\":69,\"outFeatures\":15}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":15,\"outFeatures\":15}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":15,\"outFeatures\":16}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":69,\"outFeatures\":956}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":956,\"outFeatures\":956}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":956,\"outFeatures\":16}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 326-feature input with 130 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1190\nComponents:\n - input (input) params={\"shape\":[1,326]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,326]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":326,\"outFeatures\":891}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":891,\"outFeatures\":353}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":353,\"outFeatures\":366}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":366,\"outFeatures\":698}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":698,\"outFeatures\":130}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1089-dim input: encode down to a 57-dim bottleneck and decode back to 1089. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1191\nComponents:\n - input (input) params={\"shape\":[1,1089]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1089]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1089,\"outFeatures\":687}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":687,\"outFeatures\":57}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":57,\"outFeatures\":687}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":687,\"outFeatures\":1089}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x40x40 image with 43 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1192\nComponents:\n - input (input) params={\"shape\":[1,3,40,40]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,40,40]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":35,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":35,\"outChannels\":31,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":31,\"outChannels\":62,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":62,\"outFeatures\":43}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 353-token sequences with 3 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1193\nComponents:\n - input (input) params={\"shape\":[1,353]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,353]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":18764,\"embeddingDim\":24}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":24,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":24,\"outFeatures\":3}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 505-token sequences with 75 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1194\nComponents:\n - input (input) params={\"shape\":[1,505]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,505]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":18409,\"embeddingDim\":640}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":640,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[640]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":640,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[640]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":640,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[640]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":640,\"outFeatures\":75}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (434) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-1195\nComponents:\n - input (input) params={\"shape\":[1,412]}\n - embed (embedding) params={\"numEmbeddings\":34168,\"embeddingDim\":434}\n - attn (multiHeadAttention) params={\"embedDim\":434,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":434,\"outFeatures\":2}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 3690-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1196\nComponents:\n - input (input) params={\"shape\":[1,60]}\n - fc1 (linear) params={\"inFeatures\":60,\"outFeatures\":3690}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3690,\"outFeatures\":3690}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":3690,\"outFeatures\":40}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":60,\"outFeatures\":269}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":269,\"outFeatures\":269}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":269,\"outFeatures\":40}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 166-feature, 76-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1197\nComponents:\n - input (input) params={\"shape\":[1,166]}\n - fc1 (linear) params={\"inFeatures\":166,\"outFeatures\":418}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":418,\"outFeatures\":367}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":367,\"outFeatures\":288}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":288,\"outFeatures\":231}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":231,\"outFeatures\":91}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":91,\"outFeatures\":76}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":418}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":367}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":288}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":231}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":91}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 83-feature user input and a 134-feature item input, each through its own 2-layer MLP tower ending at width 238, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1198\nComponents:\n - user_input (input) params={\"shape\":[1,83]}\n - item_input (input) params={\"shape\":[1,134]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,83]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,134]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":83,\"outFeatures\":238}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":238,\"outFeatures\":238}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":134,\"outFeatures\":238}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":238,\"outFeatures\":238}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":476,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (50-feature input, 41 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1199\nComponents:\n - input (input) params={\"shape\":[1,50]}\n - fc1 (linear) params={\"inFeatures\":50,\"outFeatures\":22}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":22,\"outFeatures\":22}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":22,\"outFeatures\":41}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":50,\"outFeatures\":690}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":690,\"outFeatures\":690}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":690,\"outFeatures\":41}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 318-feature input with 3 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1200\nComponents:\n - input (input) params={\"shape\":[1,318]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,318]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":318,\"outFeatures\":905}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":905,\"outFeatures\":680}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":680,\"outFeatures\":181}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":181,\"outFeatures\":344}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":344,\"outFeatures\":3}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1668-dim input: encode down to a 30-dim bottleneck and decode back to 1668. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1201\nComponents:\n - input (input) params={\"shape\":[1,1668]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1668]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1668,\"outFeatures\":624}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":624,\"outFeatures\":30}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":30,\"outFeatures\":624}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":624,\"outFeatures\":1668}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x38x38 image with 20 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1202\nComponents:\n - input (input) params={\"shape\":[1,3,38,38]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,38,38]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":18,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":18,\"outChannels\":33,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":33,\"outFeatures\":20}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 111-token sequences with 82 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1203\nComponents:\n - input (input) params={\"shape\":[1,111]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,111]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":22196,\"embeddingDim\":24}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":24,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":24,\"outFeatures\":82}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 146-token sequences with 63 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1204\nComponents:\n - input (input) params={\"shape\":[1,146]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,146]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":12892,\"embeddingDim\":280}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":280,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[280]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":280,\"outFeatures\":63}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (402) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-1205\nComponents:\n - input (input) params={\"shape\":[1,376]}\n - embed (embedding) params={\"numEmbeddings\":34892,\"embeddingDim\":402}\n - attn (multiHeadAttention) params={\"embedDim\":402,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":402,\"outFeatures\":74}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 2808-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1206\nComponents:\n - input (input) params={\"shape\":[1,112]}\n - fc1 (linear) params={\"inFeatures\":112,\"outFeatures\":2808}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2808,\"outFeatures\":2808}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2808,\"outFeatures\":2808}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":2808,\"outFeatures\":33}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":112,\"outFeatures\":159}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":159,\"outFeatures\":159}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":159,\"outFeatures\":159}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":159,\"outFeatures\":33}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 190-feature, 96-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1207\nComponents:\n - input (input) params={\"shape\":[1,190]}\n - fc1 (linear) params={\"inFeatures\":190,\"outFeatures\":207}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":207,\"outFeatures\":276}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":276,\"outFeatures\":509}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":509,\"outFeatures\":409}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":409,\"outFeatures\":467}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":467,\"outFeatures\":96}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":207}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":276}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":509}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":409}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":467}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 187-feature user input and a 83-feature item input, each through its own 2-layer MLP tower ending at width 241, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1208\nComponents:\n - user_input (input) params={\"shape\":[1,187]}\n - item_input (input) params={\"shape\":[1,83]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,187]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,83]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":187,\"outFeatures\":241}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":241,\"outFeatures\":241}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":83,\"outFeatures\":241}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":241,\"outFeatures\":241}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":482,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 402-feature input with 27 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1210\nComponents:\n - input (input) params={\"shape\":[1,402]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,402]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":402,\"outFeatures\":454}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":454,\"outFeatures\":216}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":216,\"outFeatures\":974}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":974,\"outFeatures\":695}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":695,\"outFeatures\":438}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":438,\"outFeatures\":27}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1939-dim input: encode down to a 58-dim bottleneck and decode back to 1939. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1211\nComponents:\n - input (input) params={\"shape\":[1,1939]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1939]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1939,\"outFeatures\":544}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":544,\"outFeatures\":58}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":58,\"outFeatures\":544}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":544,\"outFeatures\":1939}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x42x42 image with 50 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1212\nComponents:\n - input (input) params={\"shape\":[1,3,42,42]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,42,42]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":39,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":39,\"outChannels\":52,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":52,\"outFeatures\":50}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 83-token sequences with 55 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1213\nComponents:\n - input (input) params={\"shape\":[1,83]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,83]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":37850,\"embeddingDim\":344}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":344,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":344,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":344,\"outFeatures\":55}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 370-token sequences with 42 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1214\nComponents:\n - input (input) params={\"shape\":[1,370]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,370]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":34494,\"embeddingDim\":480}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":480,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[480]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":480,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[480]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":480,\"outFeatures\":42}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (68) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-1215\nComponents:\n - input (input) params={\"shape\":[1,268]}\n - embed (embedding) params={\"numEmbeddings\":13277,\"embeddingDim\":68}\n - attn (multiHeadAttention) params={\"embedDim\":68,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":68,\"outFeatures\":66}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":4}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 1596-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1216\nComponents:\n - input (input) params={\"shape\":[1,160]}\n - fc1 (linear) params={\"inFeatures\":160,\"outFeatures\":1596}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":1596,\"outFeatures\":1596}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":1596,\"outFeatures\":1596}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":1596,\"outFeatures\":1596}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":1596,\"outFeatures\":27}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":160,\"outFeatures\":219}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":219,\"outFeatures\":219}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":219,\"outFeatures\":219}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":219,\"outFeatures\":219}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":219,\"outFeatures\":27}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 92-feature, 38-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1217\nComponents:\n - input (input) params={\"shape\":[1,92]}\n - fc1 (linear) params={\"inFeatures\":92,\"outFeatures\":276}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":276,\"outFeatures\":374}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":374,\"outFeatures\":351}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":351,\"outFeatures\":93}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":93,\"outFeatures\":41}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":41,\"outFeatures\":38}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":276}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":374}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":351}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":93}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":41}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 142-feature user input and a 169-feature item input, each through its own 2-layer MLP tower ending at width 445, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1218\nComponents:\n - user_input (input) params={\"shape\":[1,142]}\n - item_input (input) params={\"shape\":[1,169]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,142]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,169]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":142,\"outFeatures\":445}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":445,\"outFeatures\":445}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":169,\"outFeatures\":445}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":445,\"outFeatures\":445}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":890,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (30-feature input, 28 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1219\nComponents:\n - input (input) params={\"shape\":[1,30]}\n - fc1 (linear) params={\"inFeatures\":30,\"outFeatures\":22}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":22,\"outFeatures\":22}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":22,\"outFeatures\":28}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":30,\"outFeatures\":650}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":650,\"outFeatures\":650}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":650,\"outFeatures\":28}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 196-feature input with 20 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1220\nComponents:\n - input (input) params={\"shape\":[1,196]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,196]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":196,\"outFeatures\":953}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":953,\"outFeatures\":831}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":831,\"outFeatures\":20}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1382-dim input: encode down to a 30-dim bottleneck and decode back to 1382. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1221\nComponents:\n - input (input) params={\"shape\":[1,1382]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1382]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1382,\"outFeatures\":301}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":301,\"outFeatures\":30}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":30,\"outFeatures\":301}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":301,\"outFeatures\":1382}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x28x28 image with 94 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1222\nComponents:\n - input (input) params={\"shape\":[1,3,28,28]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,28,28]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":15,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":15,\"outChannels\":10,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":10,\"outChannels\":48,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":48,\"outChannels\":13,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":13,\"outFeatures\":94}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 295-token sequences with 70 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1223\nComponents:\n - input (input) params={\"shape\":[1,295]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,295]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":16003,\"embeddingDim\":416}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":416,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":416,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":416,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":416,\"outFeatures\":70}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 112-token sequences with 31 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1224\nComponents:\n - input (input) params={\"shape\":[1,112]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,112]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":18767,\"embeddingDim\":80}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":80,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[80]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":80,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[80]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":80,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[80]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":80,\"outFeatures\":31}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (434) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-1225\nComponents:\n - input (input) params={\"shape\":[1,165]}\n - embed (embedding) params={\"numEmbeddings\":17125,\"embeddingDim\":434}\n - attn (multiHeadAttention) params={\"embedDim\":434,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":434,\"outFeatures\":13}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 2223-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1226\nComponents:\n - input (input) params={\"shape\":[1,225]}\n - fc1 (linear) params={\"inFeatures\":225,\"outFeatures\":2223}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2223,\"outFeatures\":2223}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2223,\"outFeatures\":2223}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":2223,\"outFeatures\":2223}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":2223,\"outFeatures\":18}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":225,\"outFeatures\":273}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":273,\"outFeatures\":273}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":273,\"outFeatures\":273}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":273,\"outFeatures\":273}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":273,\"outFeatures\":18}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 107-feature, 8-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1227\nComponents:\n - input (input) params={\"shape\":[1,107]}\n - fc1 (linear) params={\"inFeatures\":107,\"outFeatures\":417}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":417,\"outFeatures\":169}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":169,\"outFeatures\":47}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":47,\"outFeatures\":263}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":263,\"outFeatures\":315}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":315,\"outFeatures\":8}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":417}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":169}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":47}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":263}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":315}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 83-feature user input and a 32-feature item input, each through its own 2-layer MLP tower ending at width 399, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1228\nComponents:\n - user_input (input) params={\"shape\":[1,83]}\n - item_input (input) params={\"shape\":[1,32]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,83]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,32]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":83,\"outFeatures\":399}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":399,\"outFeatures\":399}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":32,\"outFeatures\":399}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":399,\"outFeatures\":399}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":798,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (99-feature input, 18 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1229\nComponents:\n - input (input) params={\"shape\":[1,99]}\n - fc1 (linear) params={\"inFeatures\":99,\"outFeatures\":14}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":14,\"outFeatures\":14}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":14,\"outFeatures\":18}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":99,\"outFeatures\":646}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":646,\"outFeatures\":646}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":646,\"outFeatures\":18}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 248-feature input with 56 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1230\nComponents:\n - input (input) params={\"shape\":[1,248]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,248]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":248,\"outFeatures\":910}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":910,\"outFeatures\":780}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":780,\"outFeatures\":606}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":606,\"outFeatures\":56}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1048-dim input: encode down to a 158-dim bottleneck and decode back to 1048. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1231\nComponents:\n - input (input) params={\"shape\":[1,1048]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1048]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1048,\"outFeatures\":737}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":737,\"outFeatures\":158}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":158,\"outFeatures\":737}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":737,\"outFeatures\":1048}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x57x57 image with 89 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1232\nComponents:\n - input (input) params={\"shape\":[1,3,57,57]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,57,57]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":22,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":22,\"outChannels\":60,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":60,\"outChannels\":39,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":39,\"outFeatures\":89}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 280-token sequences with 96 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1233\nComponents:\n - input (input) params={\"shape\":[1,280]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,280]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":25500,\"embeddingDim\":264}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":264,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":264,\"outFeatures\":96}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 378-token sequences with 57 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1234\nComponents:\n - input (input) params={\"shape\":[1,378]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,378]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":31559,\"embeddingDim\":88}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":88,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[88]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":88,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[88]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":88,\"outFeatures\":57}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3399-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1236\nComponents:\n - input (input) params={\"shape\":[1,237]}\n - fc1 (linear) params={\"inFeatures\":237,\"outFeatures\":3399}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3399,\"outFeatures\":3399}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3399,\"outFeatures\":3399}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3399,\"outFeatures\":3399}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3399,\"outFeatures\":21}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":237,\"outFeatures\":358}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":358,\"outFeatures\":358}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":358,\"outFeatures\":358}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":358,\"outFeatures\":358}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":358,\"outFeatures\":21}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 242-feature, 78-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1237\nComponents:\n - input (input) params={\"shape\":[1,242]}\n - fc1 (linear) params={\"inFeatures\":242,\"outFeatures\":167}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":167,\"outFeatures\":34}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":34,\"outFeatures\":435}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":435,\"outFeatures\":78}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":167}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":34}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":435}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 90-feature user input and a 112-feature item input, each through its own 2-layer MLP tower ending at width 369, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1238\nComponents:\n - user_input (input) params={\"shape\":[1,90]}\n - item_input (input) params={\"shape\":[1,112]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,90]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,112]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":90,\"outFeatures\":369}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":369,\"outFeatures\":369}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":112,\"outFeatures\":369}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":369,\"outFeatures\":369}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":738,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (110-feature input, 27 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1239\nComponents:\n - input (input) params={\"shape\":[1,110]}\n - fc1 (linear) params={\"inFeatures\":110,\"outFeatures\":20}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":20,\"outFeatures\":20}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":20,\"outFeatures\":27}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":110,\"outFeatures\":1201}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1201,\"outFeatures\":1201}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1201,\"outFeatures\":27}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 128-feature input with 91 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1240\nComponents:\n - input (input) params={\"shape\":[1,128]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,128]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":128,\"outFeatures\":271}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":271,\"outFeatures\":784}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":784,\"outFeatures\":731}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":731,\"outFeatures\":942}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":942,\"outFeatures\":832}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":832,\"outFeatures\":91}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 419-dim input: encode down to a 105-dim bottleneck and decode back to 419. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1241\nComponents:\n - input (input) params={\"shape\":[1,419]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,419]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":419,\"outFeatures\":723}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":723,\"outFeatures\":105}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":105,\"outFeatures\":723}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":723,\"outFeatures\":419}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x48x48 image with 61 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1242\nComponents:\n - input (input) params={\"shape\":[1,3,48,48]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,48,48]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":15,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":15,\"outChannels\":43,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":43,\"outFeatures\":61}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 445-token sequences with 83 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1243\nComponents:\n - input (input) params={\"shape\":[1,445]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,445]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":10366,\"embeddingDim\":76}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":76,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":76,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":76,\"outFeatures\":83}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 390-token sequences with 74 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1244\nComponents:\n - input (input) params={\"shape\":[1,390]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,390]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":9626,\"embeddingDim\":432}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":432,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[432]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":432,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[432]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":432,\"outFeatures\":74}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (212) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-1245\nComponents:\n - input (input) params={\"shape\":[1,94]}\n - embed (embedding) params={\"numEmbeddings\":29422,\"embeddingDim\":212}\n - attn (multiHeadAttention) params={\"embedDim\":212,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":212,\"outFeatures\":80}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":4}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 2500-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1246\nComponents:\n - input (input) params={\"shape\":[1,215]}\n - fc1 (linear) params={\"inFeatures\":215,\"outFeatures\":2500}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2500,\"outFeatures\":2500}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2500,\"outFeatures\":2500}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":2500,\"outFeatures\":17}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":215,\"outFeatures\":216}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":216,\"outFeatures\":216}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":216,\"outFeatures\":216}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":216,\"outFeatures\":17}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 162-feature, 99-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1247\nComponents:\n - input (input) params={\"shape\":[1,162]}\n - fc1 (linear) params={\"inFeatures\":162,\"outFeatures\":362}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":362,\"outFeatures\":234}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":234,\"outFeatures\":380}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":380,\"outFeatures\":478}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":478,\"outFeatures\":99}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":362}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":234}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":380}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":478}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 130-feature user input and a 59-feature item input, each through its own 2-layer MLP tower ending at width 476, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1248\nComponents:\n - user_input (input) params={\"shape\":[1,130]}\n - item_input (input) params={\"shape\":[1,59]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,130]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,59]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":130,\"outFeatures\":476}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":476,\"outFeatures\":476}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":59,\"outFeatures\":476}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":476,\"outFeatures\":476}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":952,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (17-feature input, 14 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1249\nComponents:\n - input (input) params={\"shape\":[1,17]}\n - fc1 (linear) params={\"inFeatures\":17,\"outFeatures\":8}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":8,\"outFeatures\":8}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":8,\"outFeatures\":14}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":17,\"outFeatures\":927}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":927,\"outFeatures\":927}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":927,\"outFeatures\":14}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 209-feature input with 149 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1250\nComponents:\n - input (input) params={\"shape\":[1,209]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,209]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":209,\"outFeatures\":891}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":891,\"outFeatures\":591}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":591,\"outFeatures\":25}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":25,\"outFeatures\":149}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 965-dim input: encode down to a 64-dim bottleneck and decode back to 965. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1251\nComponents:\n - input (input) params={\"shape\":[1,965]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,965]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":965,\"outFeatures\":851}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":851,\"outFeatures\":64}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":64,\"outFeatures\":851}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":851,\"outFeatures\":965}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x55x55 image with 49 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1252\nComponents:\n - input (input) params={\"shape\":[1,3,55,55]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,55,55]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":23,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":23,\"outChannels\":45,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":45,\"outChannels\":33,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":33,\"outChannels\":25,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":25,\"outFeatures\":49}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 508-token sequences with 20 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1253\nComponents:\n - input (input) params={\"shape\":[1,508]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,508]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":8587,\"embeddingDim\":240}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":240,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":240,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":240,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":240,\"outFeatures\":20}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 372-token sequences with 100 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1254\nComponents:\n - input (input) params={\"shape\":[1,372]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,372]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":24456,\"embeddingDim\":224}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":224,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[224]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":224,\"outFeatures\":100}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 2398-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1256\nComponents:\n - input (input) params={\"shape\":[1,108]}\n - fc1 (linear) params={\"inFeatures\":108,\"outFeatures\":2398}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2398,\"outFeatures\":2398}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2398,\"outFeatures\":2398}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":2398,\"outFeatures\":19}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":108,\"outFeatures\":149}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":149,\"outFeatures\":149}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":149,\"outFeatures\":149}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":149,\"outFeatures\":19}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 128-feature, 52-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1257\nComponents:\n - input (input) params={\"shape\":[1,128]}\n - fc1 (linear) params={\"inFeatures\":128,\"outFeatures\":389}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":389,\"outFeatures\":109}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":109,\"outFeatures\":259}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":259,\"outFeatures\":52}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":389}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":109}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":259}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 198-feature user input and a 240-feature item input, each through its own 2-layer MLP tower ending at width 259, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1258\nComponents:\n - user_input (input) params={\"shape\":[1,198]}\n - item_input (input) params={\"shape\":[1,240]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,198]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,240]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":198,\"outFeatures\":259}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":259,\"outFeatures\":259}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":240,\"outFeatures\":259}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":259,\"outFeatures\":259}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":518,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (121-feature input, 38 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1259\nComponents:\n - input (input) params={\"shape\":[1,121]}\n - fc1 (linear) params={\"inFeatures\":121,\"outFeatures\":4}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":4,\"outFeatures\":4}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":4,\"outFeatures\":38}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":121,\"outFeatures\":827}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":827,\"outFeatures\":827}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":827,\"outFeatures\":38}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 503-feature input with 21 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1260\nComponents:\n - input (input) params={\"shape\":[1,503]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,503]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":503,\"outFeatures\":188}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":188,\"outFeatures\":931}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":931,\"outFeatures\":942}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":942,\"outFeatures\":451}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":451,\"outFeatures\":970}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":970,\"outFeatures\":21}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 811-dim input: encode down to a 38-dim bottleneck and decode back to 811. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1261\nComponents:\n - input (input) params={\"shape\":[1,811]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,811]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":811,\"outFeatures\":133}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":133,\"outFeatures\":38}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":38,\"outFeatures\":133}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":133,\"outFeatures\":811}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x26x26 image with 45 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1262\nComponents:\n - input (input) params={\"shape\":[1,3,26,26]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,26,26]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":40,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":40,\"outChannels\":19,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":19,\"outChannels\":16,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":16,\"outFeatures\":45}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 67-token sequences with 30 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1263\nComponents:\n - input (input) params={\"shape\":[1,67]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,67]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":33379,\"embeddingDim\":288}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":288,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":288,\"outFeatures\":30}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 253-token sequences with 93 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1264\nComponents:\n - input (input) params={\"shape\":[1,253]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,253]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":10927,\"embeddingDim\":288}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":288,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[288]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":288,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[288]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":288,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[288]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":288,\"outFeatures\":93}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (326) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-1265\nComponents:\n - input (input) params={\"shape\":[1,312]}\n - embed (embedding) params={\"numEmbeddings\":8782,\"embeddingDim\":326}\n - attn (multiHeadAttention) params={\"embedDim\":326,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":326,\"outFeatures\":28}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 2247-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1266\nComponents:\n - input (input) params={\"shape\":[1,256]}\n - fc1 (linear) params={\"inFeatures\":256,\"outFeatures\":2247}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2247,\"outFeatures\":2247}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2247,\"outFeatures\":2247}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":2247,\"outFeatures\":2247}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":2247,\"outFeatures\":48}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":256,\"outFeatures\":203}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":203,\"outFeatures\":203}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":203,\"outFeatures\":203}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":203,\"outFeatures\":203}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":203,\"outFeatures\":48}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 48-feature, 31-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1267\nComponents:\n - input (input) params={\"shape\":[1,48]}\n - fc1 (linear) params={\"inFeatures\":48,\"outFeatures\":272}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":272,\"outFeatures\":230}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":230,\"outFeatures\":31}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":272}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":230}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 240-feature user input and a 113-feature item input, each through its own 2-layer MLP tower ending at width 388, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1268\nComponents:\n - user_input (input) params={\"shape\":[1,240]}\n - item_input (input) params={\"shape\":[1,113]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,240]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,113]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":240,\"outFeatures\":388}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":388,\"outFeatures\":388}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":113,\"outFeatures\":388}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":388,\"outFeatures\":388}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":776,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (45-feature input, 27 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1269\nComponents:\n - input (input) params={\"shape\":[1,45]}\n - fc1 (linear) params={\"inFeatures\":45,\"outFeatures\":13}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":13,\"outFeatures\":13}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":13,\"outFeatures\":27}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":45,\"outFeatures\":1217}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1217,\"outFeatures\":1217}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1217,\"outFeatures\":27}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 361-feature input with 136 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1270\nComponents:\n - input (input) params={\"shape\":[1,361]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,361]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":361,\"outFeatures\":485}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":485,\"outFeatures\":108}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":108,\"outFeatures\":873}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":873,\"outFeatures\":397}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":397,\"outFeatures\":987}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":987,\"outFeatures\":465}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":465,\"outFeatures\":136}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 506-dim input: encode down to a 56-dim bottleneck and decode back to 506. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1271\nComponents:\n - input (input) params={\"shape\":[1,506]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,506]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":506,\"outFeatures\":776}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":776,\"outFeatures\":56}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":56,\"outFeatures\":776}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":776,\"outFeatures\":506}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x49x49 image with 17 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1272\nComponents:\n - input (input) params={\"shape\":[1,3,49,49]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,49,49]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":15,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":15,\"outChannels\":50,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":50,\"outChannels\":21,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":21,\"outChannels\":62,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":62,\"outFeatures\":17}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 128-token sequences with 44 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1273\nComponents:\n - input (input) params={\"shape\":[1,128]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,128]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":33948,\"embeddingDim\":72}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":72,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":72,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":72,\"outFeatures\":44}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 158-token sequences with 75 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1274\nComponents:\n - input (input) params={\"shape\":[1,158]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,158]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":8529,\"embeddingDim\":264}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":264,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[264]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":264,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[264]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":264,\"outFeatures\":75}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (346) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-1275\nComponents:\n - input (input) params={\"shape\":[1,175]}\n - embed (embedding) params={\"numEmbeddings\":29189,\"embeddingDim\":346}\n - attn (multiHeadAttention) params={\"embedDim\":346,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":346,\"outFeatures\":71}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 3090-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1276\nComponents:\n - input (input) params={\"shape\":[1,122]}\n - fc1 (linear) params={\"inFeatures\":122,\"outFeatures\":3090}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3090,\"outFeatures\":3090}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3090,\"outFeatures\":3090}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":3090,\"outFeatures\":14}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":122,\"outFeatures\":134}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":134,\"outFeatures\":134}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":134,\"outFeatures\":134}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":134,\"outFeatures\":14}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 221-feature, 94-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1277\nComponents:\n - input (input) params={\"shape\":[1,221]}\n - fc1 (linear) params={\"inFeatures\":221,\"outFeatures\":259}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":259,\"outFeatures\":64}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":64,\"outFeatures\":94}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":259}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":64}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 106-feature user input and a 38-feature item input, each through its own 2-layer MLP tower ending at width 163, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1278\nComponents:\n - user_input (input) params={\"shape\":[1,106]}\n - item_input (input) params={\"shape\":[1,38]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,106]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,38]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":106,\"outFeatures\":163}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":163,\"outFeatures\":163}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":38,\"outFeatures\":163}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":163,\"outFeatures\":163}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":326,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (86-feature input, 35 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1279\nComponents:\n - input (input) params={\"shape\":[1,86]}\n - fc1 (linear) params={\"inFeatures\":86,\"outFeatures\":11}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":11,\"outFeatures\":11}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":11,\"outFeatures\":35}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":86,\"outFeatures\":803}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":803,\"outFeatures\":803}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":803,\"outFeatures\":35}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 293-feature input with 152 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1280\nComponents:\n - input (input) params={\"shape\":[1,293]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,293]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":293,\"outFeatures\":409}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":409,\"outFeatures\":257}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":257,\"outFeatures\":732}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":732,\"outFeatures\":801}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":801,\"outFeatures\":578}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":578,\"outFeatures\":152}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 969-dim input: encode down to a 224-dim bottleneck and decode back to 969. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1281\nComponents:\n - input (input) params={\"shape\":[1,969]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,969]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":969,\"outFeatures\":187}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":187,\"outFeatures\":224}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":224,\"outFeatures\":187}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":187,\"outFeatures\":969}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x55x55 image with 14 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1282\nComponents:\n - input (input) params={\"shape\":[1,3,55,55]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,55,55]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":14,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":14,\"outChannels\":57,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":57,\"outChannels\":51,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":51,\"outFeatures\":14}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 495-token sequences with 2 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1283\nComponents:\n - input (input) params={\"shape\":[1,495]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,495]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":20419,\"embeddingDim\":232}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":232,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":232,\"outFeatures\":2}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 412-token sequences with 70 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1284\nComponents:\n - input (input) params={\"shape\":[1,412]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,412]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":23396,\"embeddingDim\":272}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":272,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[272]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":272,\"outFeatures\":70}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (72) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-1285\nComponents:\n - input (input) params={\"shape\":[1,261]}\n - embed (embedding) params={\"numEmbeddings\":46756,\"embeddingDim\":72}\n - attn (multiHeadAttention) params={\"embedDim\":72,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":72,\"outFeatures\":100}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":8}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 2069-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1286\nComponents:\n - input (input) params={\"shape\":[1,143]}\n - fc1 (linear) params={\"inFeatures\":143,\"outFeatures\":2069}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2069,\"outFeatures\":2069}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2069,\"outFeatures\":2069}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":2069,\"outFeatures\":19}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":143,\"outFeatures\":196}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":196,\"outFeatures\":196}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":196,\"outFeatures\":196}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":196,\"outFeatures\":19}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 182-feature, 48-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1287\nComponents:\n - input (input) params={\"shape\":[1,182]}\n - fc1 (linear) params={\"inFeatures\":182,\"outFeatures\":115}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":115,\"outFeatures\":176}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":176,\"outFeatures\":392}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":392,\"outFeatures\":301}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":301,\"outFeatures\":82}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":82,\"outFeatures\":48}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":115}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":176}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":392}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":301}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":82}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 182-feature user input and a 87-feature item input, each through its own 2-layer MLP tower ending at width 313, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1288\nComponents:\n - user_input (input) params={\"shape\":[1,182]}\n - item_input (input) params={\"shape\":[1,87]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,182]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,87]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":182,\"outFeatures\":313}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":313,\"outFeatures\":313}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":87,\"outFeatures\":313}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":313,\"outFeatures\":313}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":626,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (99-feature input, 26 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1289\nComponents:\n - input (input) params={\"shape\":[1,99]}\n - fc1 (linear) params={\"inFeatures\":99,\"outFeatures\":17}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":17,\"outFeatures\":17}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":17,\"outFeatures\":26}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":99,\"outFeatures\":700}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":700,\"outFeatures\":700}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":700,\"outFeatures\":26}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 462-feature input with 42 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1290\nComponents:\n - input (input) params={\"shape\":[1,462]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,462]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":462,\"outFeatures\":767}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":767,\"outFeatures\":190}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":190,\"outFeatures\":700}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":700,\"outFeatures\":389}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":389,\"outFeatures\":584}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":584,\"outFeatures\":42}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 994-dim input: encode down to a 210-dim bottleneck and decode back to 994. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1291\nComponents:\n - input (input) params={\"shape\":[1,994]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,994]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":994,\"outFeatures\":905}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":905,\"outFeatures\":210}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":210,\"outFeatures\":905}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":905,\"outFeatures\":994}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x40x40 image with 45 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1292\nComponents:\n - input (input) params={\"shape\":[1,3,40,40]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,40,40]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":18,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":18,\"outChannels\":14,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":14,\"outChannels\":26,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":26,\"outFeatures\":45}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 317-token sequences with 44 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1293\nComponents:\n - input (input) params={\"shape\":[1,317]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,317]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":46357,\"embeddingDim\":180}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":180,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":180,\"outFeatures\":44}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 230-token sequences with 46 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1294\nComponents:\n - input (input) params={\"shape\":[1,230]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,230]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":14469,\"embeddingDim\":184}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":184,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[184]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":184,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[184]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":184,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[184]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":184,\"outFeatures\":46}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 1639-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1296\nComponents:\n - input (input) params={\"shape\":[1,104]}\n - fc1 (linear) params={\"inFeatures\":104,\"outFeatures\":1639}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":1639,\"outFeatures\":1639}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":1639,\"outFeatures\":1639}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":1639,\"outFeatures\":27}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":104,\"outFeatures\":294}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":294,\"outFeatures\":294}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":294,\"outFeatures\":294}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":294,\"outFeatures\":27}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 28-feature, 71-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1297\nComponents:\n - input (input) params={\"shape\":[1,28]}\n - fc1 (linear) params={\"inFeatures\":28,\"outFeatures\":194}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":194,\"outFeatures\":283}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":283,\"outFeatures\":71}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":194}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":283}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 156-feature user input and a 213-feature item input, each through its own 2-layer MLP tower ending at width 258, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1298\nComponents:\n - user_input (input) params={\"shape\":[1,156]}\n - item_input (input) params={\"shape\":[1,213]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,156]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,213]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":156,\"outFeatures\":258}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":258,\"outFeatures\":258}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":213,\"outFeatures\":258}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":258,\"outFeatures\":258}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":516,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (84-feature input, 41 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1299\nComponents:\n - input (input) params={\"shape\":[1,84]}\n - fc1 (linear) params={\"inFeatures\":84,\"outFeatures\":23}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":23,\"outFeatures\":23}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":23,\"outFeatures\":41}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":84,\"outFeatures\":1165}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1165,\"outFeatures\":1165}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1165,\"outFeatures\":41}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 118-feature input with 198 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1300\nComponents:\n - input (input) params={\"shape\":[1,118]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,118]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":118,\"outFeatures\":268}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":268,\"outFeatures\":155}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":155,\"outFeatures\":198}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1363-dim input: encode down to a 184-dim bottleneck and decode back to 1363. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1301\nComponents:\n - input (input) params={\"shape\":[1,1363]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1363]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1363,\"outFeatures\":1010}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":1010,\"outFeatures\":184}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":184,\"outFeatures\":1010}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":1010,\"outFeatures\":1363}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x34x34 image with 20 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1302\nComponents:\n - input (input) params={\"shape\":[1,3,34,34]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,34,34]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":58,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":58,\"outChannels\":49,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":49,\"outChannels\":23,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":23,\"outChannels\":25,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":25,\"outFeatures\":20}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 197-token sequences with 22 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1303\nComponents:\n - input (input) params={\"shape\":[1,197]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,197]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":32140,\"embeddingDim\":240}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":240,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":240,\"outFeatures\":22}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 206-token sequences with 54 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1304\nComponents:\n - input (input) params={\"shape\":[1,206]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,206]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":23771,\"embeddingDim\":480}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":480,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[480]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":480,\"outFeatures\":54}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 2594-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1306\nComponents:\n - input (input) params={\"shape\":[1,40]}\n - fc1 (linear) params={\"inFeatures\":40,\"outFeatures\":2594}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2594,\"outFeatures\":2594}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2594,\"outFeatures\":2594}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":2594,\"outFeatures\":39}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":40,\"outFeatures\":300}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":300,\"outFeatures\":300}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":300,\"outFeatures\":300}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":300,\"outFeatures\":39}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 48-feature, 68-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1307\nComponents:\n - input (input) params={\"shape\":[1,48]}\n - fc1 (linear) params={\"inFeatures\":48,\"outFeatures\":368}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":368,\"outFeatures\":465}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":465,\"outFeatures\":237}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":237,\"outFeatures\":55}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":55,\"outFeatures\":68}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":368}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":465}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":237}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":55}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 152-feature user input and a 240-feature item input, each through its own 2-layer MLP tower ending at width 268, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1308\nComponents:\n - user_input (input) params={\"shape\":[1,152]}\n - item_input (input) params={\"shape\":[1,240]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,152]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,240]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":152,\"outFeatures\":268}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":268,\"outFeatures\":268}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":240,\"outFeatures\":268}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":268,\"outFeatures\":268}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":536,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (81-feature input, 22 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1309\nComponents:\n - input (input) params={\"shape\":[1,81]}\n - fc1 (linear) params={\"inFeatures\":81,\"outFeatures\":13}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":13,\"outFeatures\":13}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":13,\"outFeatures\":22}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":81,\"outFeatures\":970}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":970,\"outFeatures\":970}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":970,\"outFeatures\":22}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 467-feature input with 161 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1310\nComponents:\n - input (input) params={\"shape\":[1,467]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,467]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":467,\"outFeatures\":749}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":749,\"outFeatures\":865}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":865,\"outFeatures\":161}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1420-dim input: encode down to a 133-dim bottleneck and decode back to 1420. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1311\nComponents:\n - input (input) params={\"shape\":[1,1420]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1420]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1420,\"outFeatures\":605}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":605,\"outFeatures\":133}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":133,\"outFeatures\":605}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":605,\"outFeatures\":1420}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x50x50 image with 71 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1312\nComponents:\n - input (input) params={\"shape\":[1,3,50,50]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,50,50]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":59,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":59,\"outChannels\":57,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":57,\"outChannels\":39,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":39,\"outChannels\":56,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":56,\"outFeatures\":71}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 468-token sequences with 48 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1313\nComponents:\n - input (input) params={\"shape\":[1,468]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,468]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":48975,\"embeddingDim\":96}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":96,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":96,\"outFeatures\":48}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 228-token sequences with 40 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1314\nComponents:\n - input (input) params={\"shape\":[1,228]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,228]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":27452,\"embeddingDim\":368}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":368,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[368]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":368,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[368]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":368,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[368]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":368,\"outFeatures\":40}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 2394-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1316\nComponents:\n - input (input) params={\"shape\":[1,51]}\n - fc1 (linear) params={\"inFeatures\":51,\"outFeatures\":2394}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2394,\"outFeatures\":2394}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":2394,\"outFeatures\":43}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":51,\"outFeatures\":309}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":309,\"outFeatures\":309}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":309,\"outFeatures\":43}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 198-feature, 83-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1317\nComponents:\n - input (input) params={\"shape\":[1,198]}\n - fc1 (linear) params={\"inFeatures\":198,\"outFeatures\":119}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":119,\"outFeatures\":253}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":253,\"outFeatures\":171}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":171,\"outFeatures\":83}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":119}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":253}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":171}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 114-feature user input and a 252-feature item input, each through its own 2-layer MLP tower ending at width 164, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1318\nComponents:\n - user_input (input) params={\"shape\":[1,114]}\n - item_input (input) params={\"shape\":[1,252]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,114]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,252]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":114,\"outFeatures\":164}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":164,\"outFeatures\":164}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":252,\"outFeatures\":164}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":164,\"outFeatures\":164}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":328,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (36-feature input, 33 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1319\nComponents:\n - input (input) params={\"shape\":[1,36]}\n - fc1 (linear) params={\"inFeatures\":36,\"outFeatures\":6}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":6,\"outFeatures\":6}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":6,\"outFeatures\":33}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":36,\"outFeatures\":1351}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1351,\"outFeatures\":1351}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1351,\"outFeatures\":33}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 15-feature input with 148 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1320\nComponents:\n - input (input) params={\"shape\":[1,15]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,15]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":15,\"outFeatures\":293}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":293,\"outFeatures\":605}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":605,\"outFeatures\":890}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":890,\"outFeatures\":114}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":114,\"outFeatures\":148}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1271-dim input: encode down to a 77-dim bottleneck and decode back to 1271. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1321\nComponents:\n - input (input) params={\"shape\":[1,1271]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1271]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1271,\"outFeatures\":940}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":940,\"outFeatures\":77}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":77,\"outFeatures\":940}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":940,\"outFeatures\":1271}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x38x38 image with 8 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1322\nComponents:\n - input (input) params={\"shape\":[1,3,38,38]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,38,38]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":57,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":57,\"outChannels\":13,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":13,\"outChannels\":54,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":54,\"outFeatures\":8}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 253-token sequences with 9 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1323\nComponents:\n - input (input) params={\"shape\":[1,253]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,253]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":27297,\"embeddingDim\":448}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":448,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":448,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":448,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":448,\"outFeatures\":9}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 326-token sequences with 50 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1324\nComponents:\n - input (input) params={\"shape\":[1,326]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,326]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":39942,\"embeddingDim\":384}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":384,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[384]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":384,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[384]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":384,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[384]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":384,\"outFeatures\":50}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (438) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-1325\nComponents:\n - input (input) params={\"shape\":[1,447]}\n - embed (embedding) params={\"numEmbeddings\":14991,\"embeddingDim\":438}\n - attn (multiHeadAttention) params={\"embedDim\":438,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":438,\"outFeatures\":12}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 4048-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1326\nComponents:\n - input (input) params={\"shape\":[1,217]}\n - fc1 (linear) params={\"inFeatures\":217,\"outFeatures\":4048}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":4048,\"outFeatures\":4048}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":4048,\"outFeatures\":4048}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":4048,\"outFeatures\":40}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":217,\"outFeatures\":234}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":234,\"outFeatures\":234}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":234,\"outFeatures\":234}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":234,\"outFeatures\":40}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 173-feature, 67-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1327\nComponents:\n - input (input) params={\"shape\":[1,173]}\n - fc1 (linear) params={\"inFeatures\":173,\"outFeatures\":327}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":327,\"outFeatures\":317}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":317,\"outFeatures\":235}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":235,\"outFeatures\":39}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":39,\"outFeatures\":67}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":327}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":317}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":235}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":39}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 201-feature user input and a 46-feature item input, each through its own 2-layer MLP tower ending at width 466, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1328\nComponents:\n - user_input (input) params={\"shape\":[1,201]}\n - item_input (input) params={\"shape\":[1,46]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,201]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,46]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":201,\"outFeatures\":466}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":466,\"outFeatures\":466}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":46,\"outFeatures\":466}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":466,\"outFeatures\":466}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":932,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (72-feature input, 20 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1329\nComponents:\n - input (input) params={\"shape\":[1,72]}\n - fc1 (linear) params={\"inFeatures\":72,\"outFeatures\":9}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":9,\"outFeatures\":9}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":9,\"outFeatures\":20}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":72,\"outFeatures\":899}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":899,\"outFeatures\":899}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":899,\"outFeatures\":20}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 96-feature input with 187 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1330\nComponents:\n - input (input) params={\"shape\":[1,96]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,96]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":96,\"outFeatures\":114}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":114,\"outFeatures\":1017}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":1017,\"outFeatures\":187}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1323-dim input: encode down to a 159-dim bottleneck and decode back to 1323. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1331\nComponents:\n - input (input) params={\"shape\":[1,1323]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1323]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1323,\"outFeatures\":888}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":888,\"outFeatures\":159}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":159,\"outFeatures\":888}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":888,\"outFeatures\":1323}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x55x55 image with 83 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1332\nComponents:\n - input (input) params={\"shape\":[1,3,55,55]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,55,55]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":63,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":63,\"outChannels\":20,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":20,\"outChannels\":51,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":51,\"outFeatures\":83}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 348-token sequences with 51 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1333\nComponents:\n - input (input) params={\"shape\":[1,348]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,348]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":25177,\"embeddingDim\":176}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":176,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":176,\"outFeatures\":51}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 470-token sequences with 74 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1334\nComponents:\n - input (input) params={\"shape\":[1,470]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,470]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":24247,\"embeddingDim\":720}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":720,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[720]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":720,\"outFeatures\":74}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 2529-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1336\nComponents:\n - input (input) params={\"shape\":[1,224]}\n - fc1 (linear) params={\"inFeatures\":224,\"outFeatures\":2529}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2529,\"outFeatures\":2529}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2529,\"outFeatures\":2529}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":2529,\"outFeatures\":37}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":224,\"outFeatures\":115}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":115,\"outFeatures\":115}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":115,\"outFeatures\":115}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":115,\"outFeatures\":37}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 232-feature, 87-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1337\nComponents:\n - input (input) params={\"shape\":[1,232]}\n - fc1 (linear) params={\"inFeatures\":232,\"outFeatures\":357}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":357,\"outFeatures\":190}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":190,\"outFeatures\":87}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":357}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":190}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 139-feature user input and a 183-feature item input, each through its own 2-layer MLP tower ending at width 129, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1338\nComponents:\n - user_input (input) params={\"shape\":[1,139]}\n - item_input (input) params={\"shape\":[1,183]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,139]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,183]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":139,\"outFeatures\":129}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":129,\"outFeatures\":129}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":183,\"outFeatures\":129}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":129,\"outFeatures\":129}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":258,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (52-feature input, 35 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1339\nComponents:\n - input (input) params={\"shape\":[1,52]}\n - fc1 (linear) params={\"inFeatures\":52,\"outFeatures\":15}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":15,\"outFeatures\":15}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":15,\"outFeatures\":35}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":52,\"outFeatures\":1296}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1296,\"outFeatures\":1296}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1296,\"outFeatures\":35}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 256-feature input with 162 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1340\nComponents:\n - input (input) params={\"shape\":[1,256]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,256]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":256,\"outFeatures\":588}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":588,\"outFeatures\":421}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":421,\"outFeatures\":775}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":775,\"outFeatures\":317}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":317,\"outFeatures\":789}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":789,\"outFeatures\":162}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 575-dim input: encode down to a 246-dim bottleneck and decode back to 575. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1341\nComponents:\n - input (input) params={\"shape\":[1,575]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,575]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":575,\"outFeatures\":326}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":326,\"outFeatures\":246}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":246,\"outFeatures\":326}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":326,\"outFeatures\":575}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x28x28 image with 81 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1342\nComponents:\n - input (input) params={\"shape\":[1,3,28,28]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,28,28]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":27,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":27,\"outChannels\":24,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":24,\"outChannels\":30,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":30,\"outChannels\":25,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":25,\"outFeatures\":81}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 227-token sequences with 16 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1343\nComponents:\n - input (input) params={\"shape\":[1,227]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,227]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":43565,\"embeddingDim\":34}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":34,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":34,\"outFeatures\":16}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 483-token sequences with 39 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1344\nComponents:\n - input (input) params={\"shape\":[1,483]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,483]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":23955,\"embeddingDim\":104}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":104,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[104]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":104,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[104]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":104,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[104]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":104,\"outFeatures\":39}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 3010-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1346\nComponents:\n - input (input) params={\"shape\":[1,131]}\n - fc1 (linear) params={\"inFeatures\":131,\"outFeatures\":3010}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3010,\"outFeatures\":3010}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":3010,\"outFeatures\":37}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":131,\"outFeatures\":109}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":109,\"outFeatures\":109}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":109,\"outFeatures\":37}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 71-feature, 46-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1347\nComponents:\n - input (input) params={\"shape\":[1,71]}\n - fc1 (linear) params={\"inFeatures\":71,\"outFeatures\":435}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":435,\"outFeatures\":179}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":179,\"outFeatures\":421}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":421,\"outFeatures\":276}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":276,\"outFeatures\":95}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":95,\"outFeatures\":46}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":435}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":179}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":421}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":276}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":95}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 142-feature user input and a 178-feature item input, each through its own 2-layer MLP tower ending at width 67, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1348\nComponents:\n - user_input (input) params={\"shape\":[1,142]}\n - item_input (input) params={\"shape\":[1,178]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,142]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,178]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":142,\"outFeatures\":67}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":67,\"outFeatures\":67}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":178,\"outFeatures\":67}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":67,\"outFeatures\":67}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":134,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (48-feature input, 13 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1349\nComponents:\n - input (input) params={\"shape\":[1,48]}\n - fc1 (linear) params={\"inFeatures\":48,\"outFeatures\":20}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":20,\"outFeatures\":20}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":20,\"outFeatures\":13}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":48,\"outFeatures\":914}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":914,\"outFeatures\":914}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":914,\"outFeatures\":13}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 482-feature input with 193 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1350\nComponents:\n - input (input) params={\"shape\":[1,482]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,482]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":482,\"outFeatures\":174}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":174,\"outFeatures\":816}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":816,\"outFeatures\":648}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":648,\"outFeatures\":968}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":968,\"outFeatures\":193}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 683-dim input: encode down to a 61-dim bottleneck and decode back to 683. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1351\nComponents:\n - input (input) params={\"shape\":[1,683]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,683]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":683,\"outFeatures\":869}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":869,\"outFeatures\":61}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":61,\"outFeatures\":869}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":869,\"outFeatures\":683}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x63x63 image with 11 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1352\nComponents:\n - input (input) params={\"shape\":[1,3,63,63]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,63,63]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":57,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":57,\"outChannels\":63,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":63,\"outChannels\":26,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":26,\"outFeatures\":11}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 477-token sequences with 87 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1353\nComponents:\n - input (input) params={\"shape\":[1,477]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,477]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":28019,\"embeddingDim\":216}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":216,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":216,\"outFeatures\":87}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 493-token sequences with 51 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1354\nComponents:\n - input (input) params={\"shape\":[1,493]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,493]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":10371,\"embeddingDim\":376}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":376,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[376]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":376,\"outFeatures\":51}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 1777-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1356\nComponents:\n - input (input) params={\"shape\":[1,224]}\n - fc1 (linear) params={\"inFeatures\":224,\"outFeatures\":1777}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":1777,\"outFeatures\":1777}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":1777,\"outFeatures\":1777}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":1777,\"outFeatures\":22}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":224,\"outFeatures\":332}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":332,\"outFeatures\":332}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":332,\"outFeatures\":332}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":332,\"outFeatures\":22}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 26-feature, 75-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1357\nComponents:\n - input (input) params={\"shape\":[1,26]}\n - fc1 (linear) params={\"inFeatures\":26,\"outFeatures\":206}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":206,\"outFeatures\":69}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":69,\"outFeatures\":306}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":306,\"outFeatures\":52}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":52,\"outFeatures\":75}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":206}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":69}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":306}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":52}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 157-feature user input and a 190-feature item input, each through its own 2-layer MLP tower ending at width 367, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1358\nComponents:\n - user_input (input) params={\"shape\":[1,157]}\n - item_input (input) params={\"shape\":[1,190]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,157]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,190]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":157,\"outFeatures\":367}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":367,\"outFeatures\":367}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":190,\"outFeatures\":367}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":367,\"outFeatures\":367}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":734,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (20-feature input, 26 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1359\nComponents:\n - input (input) params={\"shape\":[1,20]}\n - fc1 (linear) params={\"inFeatures\":20,\"outFeatures\":16}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":16,\"outFeatures\":16}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":16,\"outFeatures\":26}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":20,\"outFeatures\":1311}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1311,\"outFeatures\":1311}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1311,\"outFeatures\":26}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 206-feature input with 52 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1360\nComponents:\n - input (input) params={\"shape\":[1,206]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,206]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":206,\"outFeatures\":777}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":777,\"outFeatures\":767}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":767,\"outFeatures\":424}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":424,\"outFeatures\":692}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":692,\"outFeatures\":446}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":446,\"outFeatures\":509}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":509,\"outFeatures\":52}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1888-dim input: encode down to a 184-dim bottleneck and decode back to 1888. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1361\nComponents:\n - input (input) params={\"shape\":[1,1888]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1888]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1888,\"outFeatures\":211}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":211,\"outFeatures\":184}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":184,\"outFeatures\":211}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":211,\"outFeatures\":1888}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x39x39 image with 86 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1362\nComponents:\n - input (input) params={\"shape\":[1,3,39,39]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,39,39]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":47,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":47,\"outChannels\":18,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":18,\"outChannels\":27,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":27,\"outChannels\":32,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":32,\"outFeatures\":86}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 88-token sequences with 17 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1363\nComponents:\n - input (input) params={\"shape\":[1,88]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,88]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":9678,\"embeddingDim\":456}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":456,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":456,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":456,\"outFeatures\":17}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 495-token sequences with 99 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1364\nComponents:\n - input (input) params={\"shape\":[1,495]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,495]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":31045,\"embeddingDim\":128}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":128,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[128]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":128,\"outFeatures\":99}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 2077-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1366\nComponents:\n - input (input) params={\"shape\":[1,38]}\n - fc1 (linear) params={\"inFeatures\":38,\"outFeatures\":2077}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2077,\"outFeatures\":2077}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2077,\"outFeatures\":2077}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":2077,\"outFeatures\":2077}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":2077,\"outFeatures\":32}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":38,\"outFeatures\":310}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":310,\"outFeatures\":310}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":310,\"outFeatures\":310}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":310,\"outFeatures\":310}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":310,\"outFeatures\":32}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 196-feature, 47-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1367\nComponents:\n - input (input) params={\"shape\":[1,196]}\n - fc1 (linear) params={\"inFeatures\":196,\"outFeatures\":118}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":118,\"outFeatures\":67}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":67,\"outFeatures\":149}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":149,\"outFeatures\":47}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":118}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":67}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":149}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 125-feature user input and a 248-feature item input, each through its own 2-layer MLP tower ending at width 291, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1368\nComponents:\n - user_input (input) params={\"shape\":[1,125]}\n - item_input (input) params={\"shape\":[1,248]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,125]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,248]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":125,\"outFeatures\":291}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":291,\"outFeatures\":291}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":248,\"outFeatures\":291}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":291,\"outFeatures\":291}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":582,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (45-feature input, 19 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1369\nComponents:\n - input (input) params={\"shape\":[1,45]}\n - fc1 (linear) params={\"inFeatures\":45,\"outFeatures\":12}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":12,\"outFeatures\":12}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":12,\"outFeatures\":19}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":45,\"outFeatures\":1255}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1255,\"outFeatures\":1255}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1255,\"outFeatures\":19}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 321-feature input with 168 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1370\nComponents:\n - input (input) params={\"shape\":[1,321]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,321]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":321,\"outFeatures\":91}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":91,\"outFeatures\":406}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":406,\"outFeatures\":168}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1084-dim input: encode down to a 82-dim bottleneck and decode back to 1084. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1371\nComponents:\n - input (input) params={\"shape\":[1,1084]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1084]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1084,\"outFeatures\":870}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":870,\"outFeatures\":82}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":82,\"outFeatures\":870}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":870,\"outFeatures\":1084}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x48x48 image with 26 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1372\nComponents:\n - input (input) params={\"shape\":[1,3,48,48]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,48,48]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":26,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":26,\"outChannels\":14,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":14,\"outFeatures\":26}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 386-token sequences with 72 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1373\nComponents:\n - input (input) params={\"shape\":[1,386]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,386]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":37131,\"embeddingDim\":80}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":80,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":80,\"outFeatures\":72}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 418-token sequences with 80 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1374\nComponents:\n - input (input) params={\"shape\":[1,418]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,418]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":30532,\"embeddingDim\":320}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":320,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[320]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":320,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[320]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":320,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[320]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":320,\"outFeatures\":80}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (332) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-1375\nComponents:\n - input (input) params={\"shape\":[1,213]}\n - embed (embedding) params={\"numEmbeddings\":41534,\"embeddingDim\":332}\n - attn (multiHeadAttention) params={\"embedDim\":332,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":332,\"outFeatures\":54}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":4}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 3118-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1376\nComponents:\n - input (input) params={\"shape\":[1,233]}\n - fc1 (linear) params={\"inFeatures\":233,\"outFeatures\":3118}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3118,\"outFeatures\":3118}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":3118,\"outFeatures\":31}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":233,\"outFeatures\":372}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":372,\"outFeatures\":372}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":372,\"outFeatures\":31}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 182-feature, 11-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1377\nComponents:\n - input (input) params={\"shape\":[1,182]}\n - fc1 (linear) params={\"inFeatures\":182,\"outFeatures\":358}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":358,\"outFeatures\":377}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":377,\"outFeatures\":11}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":358}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":377}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 187-feature user input and a 103-feature item input, each through its own 2-layer MLP tower ending at width 82, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1378\nComponents:\n - user_input (input) params={\"shape\":[1,187]}\n - item_input (input) params={\"shape\":[1,103]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,187]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,103]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":187,\"outFeatures\":82}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":82,\"outFeatures\":82}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":103,\"outFeatures\":82}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":82,\"outFeatures\":82}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":164,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (108-feature input, 39 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1379\nComponents:\n - input (input) params={\"shape\":[1,108]}\n - fc1 (linear) params={\"inFeatures\":108,\"outFeatures\":10}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":10,\"outFeatures\":10}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":10,\"outFeatures\":39}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":108,\"outFeatures\":1361}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1361,\"outFeatures\":1361}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1361,\"outFeatures\":39}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 233-feature input with 3 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1380\nComponents:\n - input (input) params={\"shape\":[1,233]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,233]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":233,\"outFeatures\":915}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":915,\"outFeatures\":91}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":91,\"outFeatures\":735}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":735,\"outFeatures\":411}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":411,\"outFeatures\":541}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":541,\"outFeatures\":103}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":103,\"outFeatures\":3}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 281-dim input: encode down to a 169-dim bottleneck and decode back to 281. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1381\nComponents:\n - input (input) params={\"shape\":[1,281]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,281]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":281,\"outFeatures\":369}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":369,\"outFeatures\":169}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":169,\"outFeatures\":369}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":369,\"outFeatures\":281}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x31x31 image with 41 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1382\nComponents:\n - input (input) params={\"shape\":[1,3,31,31]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,31,31]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":9,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":9,\"outChannels\":45,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":45,\"outChannels\":59,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":59,\"outFeatures\":41}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 62-token sequences with 17 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1383\nComponents:\n - input (input) params={\"shape\":[1,62]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,62]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":49114,\"embeddingDim\":86}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":86,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":86,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":86,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":86,\"outFeatures\":17}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 331-token sequences with 82 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1384\nComponents:\n - input (input) params={\"shape\":[1,331]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,331]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":30355,\"embeddingDim\":368}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":368,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[368]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":368,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[368]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":368,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[368]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":368,\"outFeatures\":82}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 1942-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1386\nComponents:\n - input (input) params={\"shape\":[1,131]}\n - fc1 (linear) params={\"inFeatures\":131,\"outFeatures\":1942}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":1942,\"outFeatures\":1942}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":1942,\"outFeatures\":1942}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":1942,\"outFeatures\":1942}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":1942,\"outFeatures\":2}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":131,\"outFeatures\":266}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":266,\"outFeatures\":266}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":266,\"outFeatures\":266}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":266,\"outFeatures\":266}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":266,\"outFeatures\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 220-feature, 14-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1387\nComponents:\n - input (input) params={\"shape\":[1,220]}\n - fc1 (linear) params={\"inFeatures\":220,\"outFeatures\":60}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":60,\"outFeatures\":440}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":440,\"outFeatures\":228}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":228,\"outFeatures\":383}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":383,\"outFeatures\":14}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":60}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":440}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":228}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":383}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 186-feature user input and a 52-feature item input, each through its own 2-layer MLP tower ending at width 192, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1388\nComponents:\n - user_input (input) params={\"shape\":[1,186]}\n - item_input (input) params={\"shape\":[1,52]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,186]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,52]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":186,\"outFeatures\":192}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":192,\"outFeatures\":192}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":52,\"outFeatures\":192}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":192,\"outFeatures\":192}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":384,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (59-feature input, 29 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1389\nComponents:\n - input (input) params={\"shape\":[1,59]}\n - fc1 (linear) params={\"inFeatures\":59,\"outFeatures\":9}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":9,\"outFeatures\":9}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":9,\"outFeatures\":29}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":59,\"outFeatures\":1400}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1400,\"outFeatures\":1400}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1400,\"outFeatures\":29}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 504-feature input with 125 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1390\nComponents:\n - input (input) params={\"shape\":[1,504]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,504]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":504,\"outFeatures\":450}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":450,\"outFeatures\":274}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":274,\"outFeatures\":753}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":753,\"outFeatures\":667}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":667,\"outFeatures\":868}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":868,\"outFeatures\":168}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":168,\"outFeatures\":125}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1185-dim input: encode down to a 11-dim bottleneck and decode back to 1185. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1391\nComponents:\n - input (input) params={\"shape\":[1,1185]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1185]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1185,\"outFeatures\":816}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":816,\"outFeatures\":11}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":11,\"outFeatures\":816}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":816,\"outFeatures\":1185}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x62x62 image with 18 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1392\nComponents:\n - input (input) params={\"shape\":[1,3,62,62]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,62,62]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":48,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":48,\"outChannels\":62,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":62,\"outFeatures\":18}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 111-token sequences with 57 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1393\nComponents:\n - input (input) params={\"shape\":[1,111]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,111]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":27534,\"embeddingDim\":66}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":66,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":66,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":66,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":66,\"outFeatures\":57}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 397-token sequences with 59 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1394\nComponents:\n - input (input) params={\"shape\":[1,397]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,397]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":12354,\"embeddingDim\":304}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":304,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[304]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":304,\"outFeatures\":59}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3539-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1396\nComponents:\n - input (input) params={\"shape\":[1,206]}\n - fc1 (linear) params={\"inFeatures\":206,\"outFeatures\":3539}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3539,\"outFeatures\":3539}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3539,\"outFeatures\":3539}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3539,\"outFeatures\":3539}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3539,\"outFeatures\":49}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":206,\"outFeatures\":335}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":335,\"outFeatures\":335}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":335,\"outFeatures\":335}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":335,\"outFeatures\":335}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":335,\"outFeatures\":49}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 233-feature, 63-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1397\nComponents:\n - input (input) params={\"shape\":[1,233]}\n - fc1 (linear) params={\"inFeatures\":233,\"outFeatures\":503}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":503,\"outFeatures\":348}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":348,\"outFeatures\":386}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":386,\"outFeatures\":63}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":503}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":348}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":386}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 143-feature user input and a 129-feature item input, each through its own 2-layer MLP tower ending at width 174, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1398\nComponents:\n - user_input (input) params={\"shape\":[1,143]}\n - item_input (input) params={\"shape\":[1,129]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,143]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,129]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":143,\"outFeatures\":174}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":174,\"outFeatures\":174}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":129,\"outFeatures\":174}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":174,\"outFeatures\":174}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":348,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (49-feature input, 28 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1399\nComponents:\n - input (input) params={\"shape\":[1,49]}\n - fc1 (linear) params={\"inFeatures\":49,\"outFeatures\":13}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":13,\"outFeatures\":13}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":13,\"outFeatures\":28}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":49,\"outFeatures\":787}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":787,\"outFeatures\":787}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":787,\"outFeatures\":28}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 242-feature input with 12 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1400\nComponents:\n - input (input) params={\"shape\":[1,242]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,242]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":242,\"outFeatures\":996}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":996,\"outFeatures\":713}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":713,\"outFeatures\":12}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1443-dim input: encode down to a 94-dim bottleneck and decode back to 1443. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1401\nComponents:\n - input (input) params={\"shape\":[1,1443]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1443]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1443,\"outFeatures\":574}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":574,\"outFeatures\":94}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":94,\"outFeatures\":574}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":574,\"outFeatures\":1443}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x54x54 image with 28 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1402\nComponents:\n - input (input) params={\"shape\":[1,3,54,54]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,54,54]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":22,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":22,\"outChannels\":20,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":20,\"outFeatures\":28}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 134-token sequences with 14 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1403\nComponents:\n - input (input) params={\"shape\":[1,134]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,134]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":45548,\"embeddingDim\":148}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":148,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":148,\"outFeatures\":14}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 104-token sequences with 28 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1404\nComponents:\n - input (input) params={\"shape\":[1,104]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,104]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":24454,\"embeddingDim\":592}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":592,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[592]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":592,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[592]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":592,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[592]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":592,\"outFeatures\":28}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3247-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1406\nComponents:\n - input (input) params={\"shape\":[1,134]}\n - fc1 (linear) params={\"inFeatures\":134,\"outFeatures\":3247}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3247,\"outFeatures\":3247}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3247,\"outFeatures\":3247}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3247,\"outFeatures\":3247}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3247,\"outFeatures\":8}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":134,\"outFeatures\":269}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":269,\"outFeatures\":269}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":269,\"outFeatures\":269}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":269,\"outFeatures\":269}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":269,\"outFeatures\":8}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 106-feature, 69-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1407\nComponents:\n - input (input) params={\"shape\":[1,106]}\n - fc1 (linear) params={\"inFeatures\":106,\"outFeatures\":507}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":507,\"outFeatures\":462}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":462,\"outFeatures\":69}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":507}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":462}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 98-feature user input and a 20-feature item input, each through its own 2-layer MLP tower ending at width 128, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1408\nComponents:\n - user_input (input) params={\"shape\":[1,98]}\n - item_input (input) params={\"shape\":[1,20]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,98]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,20]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":98,\"outFeatures\":128}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":128,\"outFeatures\":128}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":20,\"outFeatures\":128}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":128,\"outFeatures\":128}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":256,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (46-feature input, 15 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1409\nComponents:\n - input (input) params={\"shape\":[1,46]}\n - fc1 (linear) params={\"inFeatures\":46,\"outFeatures\":11}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":11,\"outFeatures\":11}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":11,\"outFeatures\":15}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":46,\"outFeatures\":739}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":739,\"outFeatures\":739}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":739,\"outFeatures\":15}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 173-feature input with 144 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1410\nComponents:\n - input (input) params={\"shape\":[1,173]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,173]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":173,\"outFeatures\":242}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":242,\"outFeatures\":729}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":729,\"outFeatures\":438}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":438,\"outFeatures\":779}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":779,\"outFeatures\":117}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":117,\"outFeatures\":144}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 2007-dim input: encode down to a 53-dim bottleneck and decode back to 2007. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1411\nComponents:\n - input (input) params={\"shape\":[1,2007]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,2007]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":2007,\"outFeatures\":1011}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":1011,\"outFeatures\":53}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":53,\"outFeatures\":1011}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":1011,\"outFeatures\":2007}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x34x34 image with 18 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1412\nComponents:\n - input (input) params={\"shape\":[1,3,34,34]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,34,34]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":57,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":57,\"outChannels\":54,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":54,\"outChannels\":32,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":32,\"outFeatures\":18}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 319-token sequences with 49 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1413\nComponents:\n - input (input) params={\"shape\":[1,319]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,319]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":31381,\"embeddingDim\":98}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":98,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":98,\"outFeatures\":49}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 494-token sequences with 29 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1414\nComponents:\n - input (input) params={\"shape\":[1,494]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,494]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":9741,\"embeddingDim\":184}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":184,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[184]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":184,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[184]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":184,\"outFeatures\":29}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 2978-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1416\nComponents:\n - input (input) params={\"shape\":[1,246]}\n - fc1 (linear) params={\"inFeatures\":246,\"outFeatures\":2978}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2978,\"outFeatures\":2978}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":2978,\"outFeatures\":37}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":246,\"outFeatures\":207}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":207,\"outFeatures\":207}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":207,\"outFeatures\":37}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 27-feature, 3-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1417\nComponents:\n - input (input) params={\"shape\":[1,27]}\n - fc1 (linear) params={\"inFeatures\":27,\"outFeatures\":337}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":337,\"outFeatures\":263}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":263,\"outFeatures\":63}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":63,\"outFeatures\":477}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":477,\"outFeatures\":3}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":337}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":263}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":63}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":477}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 225-feature user input and a 162-feature item input, each through its own 2-layer MLP tower ending at width 364, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1418\nComponents:\n - user_input (input) params={\"shape\":[1,225]}\n - item_input (input) params={\"shape\":[1,162]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,225]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,162]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":225,\"outFeatures\":364}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":364,\"outFeatures\":364}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":162,\"outFeatures\":364}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":364,\"outFeatures\":364}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":728,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (118-feature input, 3 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1419\nComponents:\n - input (input) params={\"shape\":[1,118]}\n - fc1 (linear) params={\"inFeatures\":118,\"outFeatures\":6}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":6,\"outFeatures\":6}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":6,\"outFeatures\":3}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":118,\"outFeatures\":1289}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1289,\"outFeatures\":1289}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1289,\"outFeatures\":3}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 192-feature input with 169 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1420\nComponents:\n - input (input) params={\"shape\":[1,192]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,192]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":192,\"outFeatures\":341}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":341,\"outFeatures\":438}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":438,\"outFeatures\":749}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":749,\"outFeatures\":225}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":225,\"outFeatures\":640}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":640,\"outFeatures\":169}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1441-dim input: encode down to a 50-dim bottleneck and decode back to 1441. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1421\nComponents:\n - input (input) params={\"shape\":[1,1441]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1441]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1441,\"outFeatures\":462}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":462,\"outFeatures\":50}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":50,\"outFeatures\":462}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":462,\"outFeatures\":1441}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x24x24 image with 77 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1422\nComponents:\n - input (input) params={\"shape\":[1,3,24,24]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,24,24]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":14,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":14,\"outChannels\":31,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":31,\"outChannels\":24,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":24,\"outFeatures\":77}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 451-token sequences with 43 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1423\nComponents:\n - input (input) params={\"shape\":[1,451]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,451]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":24055,\"embeddingDim\":64}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":64,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":64,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":64,\"outFeatures\":43}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 495-token sequences with 59 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1424\nComponents:\n - input (input) params={\"shape\":[1,495]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,495]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":37850,\"embeddingDim\":76}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":76,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[76]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":76,\"outFeatures\":59}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (494) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-1425\nComponents:\n - input (input) params={\"shape\":[1,71]}\n - embed (embedding) params={\"numEmbeddings\":10055,\"embeddingDim\":494}\n - attn (multiHeadAttention) params={\"embedDim\":494,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":494,\"outFeatures\":9}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 3533-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1426\nComponents:\n - input (input) params={\"shape\":[1,184]}\n - fc1 (linear) params={\"inFeatures\":184,\"outFeatures\":3533}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3533,\"outFeatures\":3533}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3533,\"outFeatures\":3533}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":3533,\"outFeatures\":36}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":184,\"outFeatures\":134}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":134,\"outFeatures\":134}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":134,\"outFeatures\":134}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":134,\"outFeatures\":36}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 127-feature, 9-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1427\nComponents:\n - input (input) params={\"shape\":[1,127]}\n - fc1 (linear) params={\"inFeatures\":127,\"outFeatures\":174}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":174,\"outFeatures\":78}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":78,\"outFeatures\":149}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":149,\"outFeatures\":493}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":493,\"outFeatures\":9}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":174}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":78}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":149}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":493}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 117-feature user input and a 229-feature item input, each through its own 2-layer MLP tower ending at width 302, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1428\nComponents:\n - user_input (input) params={\"shape\":[1,117]}\n - item_input (input) params={\"shape\":[1,229]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,117]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,229]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":117,\"outFeatures\":302}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":302,\"outFeatures\":302}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":229,\"outFeatures\":302}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":302,\"outFeatures\":302}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":604,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (85-feature input, 14 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1429\nComponents:\n - input (input) params={\"shape\":[1,85]}\n - fc1 (linear) params={\"inFeatures\":85,\"outFeatures\":18}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":18,\"outFeatures\":18}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":18,\"outFeatures\":14}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":85,\"outFeatures\":1004}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1004,\"outFeatures\":1004}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1004,\"outFeatures\":14}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 147-feature input with 129 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1430\nComponents:\n - input (input) params={\"shape\":[1,147]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,147]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":147,\"outFeatures\":516}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":516,\"outFeatures\":129}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":129,\"outFeatures\":275}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":275,\"outFeatures\":652}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":652,\"outFeatures\":996}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":996,\"outFeatures\":826}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":826,\"outFeatures\":129}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 64-dim input: encode down to a 153-dim bottleneck and decode back to 64. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1431\nComponents:\n - input (input) params={\"shape\":[1,64]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,64]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":64,\"outFeatures\":641}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":641,\"outFeatures\":153}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":153,\"outFeatures\":641}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":641,\"outFeatures\":64}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x43x43 image with 83 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1432\nComponents:\n - input (input) params={\"shape\":[1,3,43,43]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,43,43]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":60,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":60,\"outChannels\":64,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":64,\"outChannels\":15,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":15,\"outFeatures\":83}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 482-token sequences with 43 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1433\nComponents:\n - input (input) params={\"shape\":[1,482]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,482]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":25656,\"embeddingDim\":208}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":208,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":208,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":208,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":208,\"outFeatures\":43}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 333-token sequences with 70 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1434\nComponents:\n - input (input) params={\"shape\":[1,333]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,333]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":15273,\"embeddingDim\":96}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":96,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[96]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":96,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[96]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":96,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[96]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":96,\"outFeatures\":70}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (284) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-1435\nComponents:\n - input (input) params={\"shape\":[1,183]}\n - embed (embedding) params={\"numEmbeddings\":44636,\"embeddingDim\":284}\n - attn (multiHeadAttention) params={\"embedDim\":284,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":284,\"outFeatures\":16}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":4}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 2285-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1436\nComponents:\n - input (input) params={\"shape\":[1,123]}\n - fc1 (linear) params={\"inFeatures\":123,\"outFeatures\":2285}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2285,\"outFeatures\":2285}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2285,\"outFeatures\":2285}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":2285,\"outFeatures\":29}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":123,\"outFeatures\":382}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":382,\"outFeatures\":382}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":382,\"outFeatures\":382}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":382,\"outFeatures\":29}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 137-feature, 30-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1437\nComponents:\n - input (input) params={\"shape\":[1,137]}\n - fc1 (linear) params={\"inFeatures\":137,\"outFeatures\":47}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":47,\"outFeatures\":300}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":300,\"outFeatures\":501}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":501,\"outFeatures\":441}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":441,\"outFeatures\":30}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":47}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":300}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":501}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":441}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 140-feature user input and a 125-feature item input, each through its own 2-layer MLP tower ending at width 271, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1438\nComponents:\n - user_input (input) params={\"shape\":[1,140]}\n - item_input (input) params={\"shape\":[1,125]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,140]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,125]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":140,\"outFeatures\":271}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":271,\"outFeatures\":271}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":125,\"outFeatures\":271}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":271,\"outFeatures\":271}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":542,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (99-feature input, 18 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1439\nComponents:\n - input (input) params={\"shape\":[1,99]}\n - fc1 (linear) params={\"inFeatures\":99,\"outFeatures\":19}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":19,\"outFeatures\":19}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":19,\"outFeatures\":18}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":99,\"outFeatures\":1089}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1089,\"outFeatures\":1089}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1089,\"outFeatures\":18}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 249-feature input with 77 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1440\nComponents:\n - input (input) params={\"shape\":[1,249]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,249]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":249,\"outFeatures\":868}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":868,\"outFeatures\":187}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":187,\"outFeatures\":77}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1790-dim input: encode down to a 117-dim bottleneck and decode back to 1790. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1441\nComponents:\n - input (input) params={\"shape\":[1,1790]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1790]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1790,\"outFeatures\":408}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":408,\"outFeatures\":117}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":117,\"outFeatures\":408}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":408,\"outFeatures\":1790}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x33x33 image with 20 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1442\nComponents:\n - input (input) params={\"shape\":[1,3,33,33]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,33,33]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":9,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":9,\"outChannels\":62,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":62,\"outChannels\":45,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":45,\"outChannels\":14,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":14,\"outFeatures\":20}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 269-token sequences with 26 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1443\nComponents:\n - input (input) params={\"shape\":[1,269]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,269]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":25956,\"embeddingDim\":100}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":100,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":100,\"outFeatures\":26}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 59-token sequences with 12 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1444\nComponents:\n - input (input) params={\"shape\":[1,59]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,59]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":19989,\"embeddingDim\":48}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":48,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[48]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":48,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[48]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":48,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[48]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":48,\"outFeatures\":12}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (88) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-1445\nComponents:\n - input (input) params={\"shape\":[1,225]}\n - embed (embedding) params={\"numEmbeddings\":25132,\"embeddingDim\":88}\n - attn (multiHeadAttention) params={\"embedDim\":88,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":88,\"outFeatures\":4}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":8}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 2892-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1446\nComponents:\n - input (input) params={\"shape\":[1,107]}\n - fc1 (linear) params={\"inFeatures\":107,\"outFeatures\":2892}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2892,\"outFeatures\":2892}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2892,\"outFeatures\":2892}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":2892,\"outFeatures\":2892}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":2892,\"outFeatures\":41}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":107,\"outFeatures\":81}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":81,\"outFeatures\":81}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":81,\"outFeatures\":81}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":81,\"outFeatures\":81}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":81,\"outFeatures\":41}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 61-feature, 22-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1447\nComponents:\n - input (input) params={\"shape\":[1,61]}\n - fc1 (linear) params={\"inFeatures\":61,\"outFeatures\":388}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":388,\"outFeatures\":106}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":106,\"outFeatures\":124}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":124,\"outFeatures\":22}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":388}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":106}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":124}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 112-feature user input and a 242-feature item input, each through its own 2-layer MLP tower ending at width 273, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1448\nComponents:\n - user_input (input) params={\"shape\":[1,112]}\n - item_input (input) params={\"shape\":[1,242]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,112]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,242]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":112,\"outFeatures\":273}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":273,\"outFeatures\":273}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":242,\"outFeatures\":273}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":273,\"outFeatures\":273}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":546,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (127-feature input, 35 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1449\nComponents:\n - input (input) params={\"shape\":[1,127]}\n - fc1 (linear) params={\"inFeatures\":127,\"outFeatures\":13}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":13,\"outFeatures\":13}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":13,\"outFeatures\":35}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":127,\"outFeatures\":684}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":684,\"outFeatures\":684}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":684,\"outFeatures\":35}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 308-feature input with 19 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1450\nComponents:\n - input (input) params={\"shape\":[1,308]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,308]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":308,\"outFeatures\":986}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":986,\"outFeatures\":107}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":107,\"outFeatures\":76}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":76,\"outFeatures\":429}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":429,\"outFeatures\":19}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 328-dim input: encode down to a 53-dim bottleneck and decode back to 328. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1451\nComponents:\n - input (input) params={\"shape\":[1,328]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,328]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":328,\"outFeatures\":814}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":814,\"outFeatures\":53}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":53,\"outFeatures\":814}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":814,\"outFeatures\":328}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x56x56 image with 44 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1452\nComponents:\n - input (input) params={\"shape\":[1,3,56,56]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,56,56]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":43,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":43,\"outChannels\":63,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":63,\"outFeatures\":44}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 419-token sequences with 43 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1453\nComponents:\n - input (input) params={\"shape\":[1,419]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,419]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":8664,\"embeddingDim\":50}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":50,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":50,\"outFeatures\":43}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 423-token sequences with 77 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1454\nComponents:\n - input (input) params={\"shape\":[1,423]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,423]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":42348,\"embeddingDim\":184}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":184,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[184]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":184,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[184]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":184,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[184]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":184,\"outFeatures\":77}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3294-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1456\nComponents:\n - input (input) params={\"shape\":[1,241]}\n - fc1 (linear) params={\"inFeatures\":241,\"outFeatures\":3294}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3294,\"outFeatures\":3294}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3294,\"outFeatures\":3294}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3294,\"outFeatures\":3294}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3294,\"outFeatures\":50}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":241,\"outFeatures\":203}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":203,\"outFeatures\":203}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":203,\"outFeatures\":203}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":203,\"outFeatures\":203}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":203,\"outFeatures\":50}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 116-feature, 66-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1457\nComponents:\n - input (input) params={\"shape\":[1,116]}\n - fc1 (linear) params={\"inFeatures\":116,\"outFeatures\":503}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":503,\"outFeatures\":214}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":214,\"outFeatures\":66}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":503}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":214}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 154-feature user input and a 231-feature item input, each through its own 2-layer MLP tower ending at width 71, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1458\nComponents:\n - user_input (input) params={\"shape\":[1,154]}\n - item_input (input) params={\"shape\":[1,231]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,154]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,231]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":154,\"outFeatures\":71}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":71,\"outFeatures\":71}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":231,\"outFeatures\":71}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":71,\"outFeatures\":71}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":142,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (29-feature input, 42 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1459\nComponents:\n - input (input) params={\"shape\":[1,29]}\n - fc1 (linear) params={\"inFeatures\":29,\"outFeatures\":8}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":8,\"outFeatures\":8}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":8,\"outFeatures\":42}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":29,\"outFeatures\":843}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":843,\"outFeatures\":843}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":843,\"outFeatures\":42}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 274-feature input with 195 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1460\nComponents:\n - input (input) params={\"shape\":[1,274]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,274]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":274,\"outFeatures\":663}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":663,\"outFeatures\":475}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":475,\"outFeatures\":195}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1740-dim input: encode down to a 19-dim bottleneck and decode back to 1740. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1461\nComponents:\n - input (input) params={\"shape\":[1,1740]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1740]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1740,\"outFeatures\":173}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":173,\"outFeatures\":19}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":19,\"outFeatures\":173}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":173,\"outFeatures\":1740}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x44x44 image with 13 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1462\nComponents:\n - input (input) params={\"shape\":[1,3,44,44]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,44,44]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":18,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":18,\"outChannels\":41,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":41,\"outChannels\":28,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":28,\"outChannels\":24,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":24,\"outFeatures\":13}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 323-token sequences with 63 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1463\nComponents:\n - input (input) params={\"shape\":[1,323]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,323]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":18842,\"embeddingDim\":144}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":144,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":144,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":144,\"outFeatures\":63}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 445-token sequences with 80 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1464\nComponents:\n - input (input) params={\"shape\":[1,445]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,445]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":13229,\"embeddingDim\":96}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":96,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[96]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":96,\"outFeatures\":80}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (140) is not divisible by numHeads (11). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-1465\nComponents:\n - input (input) params={\"shape\":[1,487]}\n - embed (embedding) params={\"numEmbeddings\":31139,\"embeddingDim\":140}\n - attn (multiHeadAttention) params={\"embedDim\":140,\"numHeads\":11}\n - head (linear) params={\"inFeatures\":140,\"outFeatures\":49}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":4}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 1590-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1466\nComponents:\n - input (input) params={\"shape\":[1,239]}\n - fc1 (linear) params={\"inFeatures\":239,\"outFeatures\":1590}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":1590,\"outFeatures\":1590}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":1590,\"outFeatures\":1590}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":1590,\"outFeatures\":48}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":239,\"outFeatures\":189}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":189,\"outFeatures\":189}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":189,\"outFeatures\":189}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":189,\"outFeatures\":48}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 233-feature, 99-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1467\nComponents:\n - input (input) params={\"shape\":[1,233]}\n - fc1 (linear) params={\"inFeatures\":233,\"outFeatures\":231}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":231,\"outFeatures\":397}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":397,\"outFeatures\":99}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":231}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":397}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 203-feature user input and a 233-feature item input, each through its own 2-layer MLP tower ending at width 80, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1468\nComponents:\n - user_input (input) params={\"shape\":[1,203]}\n - item_input (input) params={\"shape\":[1,233]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,203]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,233]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":203,\"outFeatures\":80}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":80,\"outFeatures\":80}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":233,\"outFeatures\":80}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":80,\"outFeatures\":80}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":160,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (108-feature input, 49 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1469\nComponents:\n - input (input) params={\"shape\":[1,108]}\n - fc1 (linear) params={\"inFeatures\":108,\"outFeatures\":20}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":20,\"outFeatures\":20}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":20,\"outFeatures\":49}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":108,\"outFeatures\":1169}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1169,\"outFeatures\":1169}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1169,\"outFeatures\":49}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 393-feature input with 111 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1470\nComponents:\n - input (input) params={\"shape\":[1,393]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,393]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":393,\"outFeatures\":703}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":703,\"outFeatures\":615}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":615,\"outFeatures\":111}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 867-dim input: encode down to a 29-dim bottleneck and decode back to 867. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1471\nComponents:\n - input (input) params={\"shape\":[1,867]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,867]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":867,\"outFeatures\":326}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":326,\"outFeatures\":29}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":29,\"outFeatures\":326}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":326,\"outFeatures\":867}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x36x36 image with 95 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1472\nComponents:\n - input (input) params={\"shape\":[1,3,36,36]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,36,36]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":45,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":45,\"outChannels\":14,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":14,\"outChannels\":16,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":16,\"outChannels\":26,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":26,\"outFeatures\":95}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 387-token sequences with 22 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1473\nComponents:\n - input (input) params={\"shape\":[1,387]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,387]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":46906,\"embeddingDim\":60}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":60,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":60,\"outFeatures\":22}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 169-token sequences with 71 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1474\nComponents:\n - input (input) params={\"shape\":[1,169]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,169]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":23930,\"embeddingDim\":184}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":184,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[184]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":184,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[184]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":184,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[184]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":184,\"outFeatures\":71}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (126) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-1475\nComponents:\n - input (input) params={\"shape\":[1,477]}\n - embed (embedding) params={\"numEmbeddings\":35484,\"embeddingDim\":126}\n - attn (multiHeadAttention) params={\"embedDim\":126,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":126,\"outFeatures\":40}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 1691-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1476\nComponents:\n - input (input) params={\"shape\":[1,67]}\n - fc1 (linear) params={\"inFeatures\":67,\"outFeatures\":1691}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":1691,\"outFeatures\":1691}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":1691,\"outFeatures\":1691}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":1691,\"outFeatures\":36}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":67,\"outFeatures\":255}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":255,\"outFeatures\":255}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":255,\"outFeatures\":255}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":255,\"outFeatures\":36}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 226-feature, 34-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1477\nComponents:\n - input (input) params={\"shape\":[1,226]}\n - fc1 (linear) params={\"inFeatures\":226,\"outFeatures\":43}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":43,\"outFeatures\":403}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":403,\"outFeatures\":482}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":482,\"outFeatures\":496}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":496,\"outFeatures\":341}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":341,\"outFeatures\":34}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":43}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":403}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":482}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":496}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":341}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 236-feature user input and a 207-feature item input, each through its own 2-layer MLP tower ending at width 399, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1478\nComponents:\n - user_input (input) params={\"shape\":[1,236]}\n - item_input (input) params={\"shape\":[1,207]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,236]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,207]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":236,\"outFeatures\":399}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":399,\"outFeatures\":399}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":207,\"outFeatures\":399}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":399,\"outFeatures\":399}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":798,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (44-feature input, 48 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1479\nComponents:\n - input (input) params={\"shape\":[1,44]}\n - fc1 (linear) params={\"inFeatures\":44,\"outFeatures\":19}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":19,\"outFeatures\":19}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":19,\"outFeatures\":48}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":44,\"outFeatures\":766}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":766,\"outFeatures\":766}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":766,\"outFeatures\":48}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 446-feature input with 45 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1480\nComponents:\n - input (input) params={\"shape\":[1,446]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,446]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":446,\"outFeatures\":576}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":576,\"outFeatures\":831}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":831,\"outFeatures\":45}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1709-dim input: encode down to a 252-dim bottleneck and decode back to 1709. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1481\nComponents:\n - input (input) params={\"shape\":[1,1709]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1709]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1709,\"outFeatures\":289}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":289,\"outFeatures\":252}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":252,\"outFeatures\":289}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":289,\"outFeatures\":1709}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x41x41 image with 60 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1482\nComponents:\n - input (input) params={\"shape\":[1,3,41,41]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,41,41]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":18,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":18,\"outChannels\":56,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":56,\"outFeatures\":60}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 193-token sequences with 5 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1483\nComponents:\n - input (input) params={\"shape\":[1,193]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,193]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":36681,\"embeddingDim\":144}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":144,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":144,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":144,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":144,\"outFeatures\":5}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 201-token sequences with 55 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1484\nComponents:\n - input (input) params={\"shape\":[1,201]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,201]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":11205,\"embeddingDim\":752}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":752,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[752]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":752,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[752]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":752,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[752]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":752,\"outFeatures\":55}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (324) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-1485\nComponents:\n - input (input) params={\"shape\":[1,441]}\n - embed (embedding) params={\"numEmbeddings\":38444,\"embeddingDim\":324}\n - attn (multiHeadAttention) params={\"embedDim\":324,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":324,\"outFeatures\":60}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":4}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 2757-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1486\nComponents:\n - input (input) params={\"shape\":[1,203]}\n - fc1 (linear) params={\"inFeatures\":203,\"outFeatures\":2757}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2757,\"outFeatures\":2757}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2757,\"outFeatures\":2757}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":2757,\"outFeatures\":2757}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":2757,\"outFeatures\":37}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":203,\"outFeatures\":148}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":148,\"outFeatures\":148}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":148,\"outFeatures\":148}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":148,\"outFeatures\":148}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":148,\"outFeatures\":37}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 35-feature, 57-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1487\nComponents:\n - input (input) params={\"shape\":[1,35]}\n - fc1 (linear) params={\"inFeatures\":35,\"outFeatures\":188}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":188,\"outFeatures\":35}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":35,\"outFeatures\":33}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":33,\"outFeatures\":458}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":458,\"outFeatures\":57}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":188}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":35}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":33}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":458}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 215-feature user input and a 35-feature item input, each through its own 2-layer MLP tower ending at width 448, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1488\nComponents:\n - user_input (input) params={\"shape\":[1,215]}\n - item_input (input) params={\"shape\":[1,35]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,215]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,35]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":215,\"outFeatures\":448}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":448,\"outFeatures\":448}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":35,\"outFeatures\":448}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":448,\"outFeatures\":448}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":896,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (72-feature input, 34 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1489\nComponents:\n - input (input) params={\"shape\":[1,72]}\n - fc1 (linear) params={\"inFeatures\":72,\"outFeatures\":8}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":8,\"outFeatures\":8}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":8,\"outFeatures\":34}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":72,\"outFeatures\":1018}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1018,\"outFeatures\":1018}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1018,\"outFeatures\":34}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 119-feature input with 131 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1490\nComponents:\n - input (input) params={\"shape\":[1,119]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,119]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":119,\"outFeatures\":34}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":34,\"outFeatures\":351}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":351,\"outFeatures\":851}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":851,\"outFeatures\":633}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":633,\"outFeatures\":48}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":48,\"outFeatures\":131}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1484-dim input: encode down to a 118-dim bottleneck and decode back to 1484. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1491\nComponents:\n - input (input) params={\"shape\":[1,1484]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1484]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1484,\"outFeatures\":383}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":383,\"outFeatures\":118}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":118,\"outFeatures\":383}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":383,\"outFeatures\":1484}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x49x49 image with 87 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1492\nComponents:\n - input (input) params={\"shape\":[1,3,49,49]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,49,49]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":34,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":34,\"outChannels\":37,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":37,\"outChannels\":10,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":10,\"outFeatures\":87}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 367-token sequences with 7 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1493\nComponents:\n - input (input) params={\"shape\":[1,367]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,367]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":34518,\"embeddingDim\":104}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":104,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":104,\"outFeatures\":7}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 97-token sequences with 97 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1494\nComponents:\n - input (input) params={\"shape\":[1,97]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,97]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":8265,\"embeddingDim\":624}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":624,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[624]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":624,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[624]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":624,\"outFeatures\":97}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (338) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-1495\nComponents:\n - input (input) params={\"shape\":[1,39]}\n - embed (embedding) params={\"numEmbeddings\":12727,\"embeddingDim\":338}\n - attn (multiHeadAttention) params={\"embedDim\":338,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":338,\"outFeatures\":15}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 2980-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1496\nComponents:\n - input (input) params={\"shape\":[1,42]}\n - fc1 (linear) params={\"inFeatures\":42,\"outFeatures\":2980}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2980,\"outFeatures\":2980}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2980,\"outFeatures\":2980}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":2980,\"outFeatures\":4}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":42,\"outFeatures\":74}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":74,\"outFeatures\":74}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":74,\"outFeatures\":74}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":74,\"outFeatures\":4}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 91-feature, 99-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1497\nComponents:\n - input (input) params={\"shape\":[1,91]}\n - fc1 (linear) params={\"inFeatures\":91,\"outFeatures\":435}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":435,\"outFeatures\":276}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":276,\"outFeatures\":419}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":419,\"outFeatures\":99}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":435}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":276}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":419}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 127-feature user input and a 73-feature item input, each through its own 2-layer MLP tower ending at width 176, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1498\nComponents:\n - user_input (input) params={\"shape\":[1,127]}\n - item_input (input) params={\"shape\":[1,73]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,127]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,73]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":127,\"outFeatures\":176}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":176,\"outFeatures\":176}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":73,\"outFeatures\":176}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":176,\"outFeatures\":176}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":352,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (46-feature input, 8 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1499\nComponents:\n - input (input) params={\"shape\":[1,46]}\n - fc1 (linear) params={\"inFeatures\":46,\"outFeatures\":15}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":15,\"outFeatures\":15}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":15,\"outFeatures\":8}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":46,\"outFeatures\":1255}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1255,\"outFeatures\":1255}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1255,\"outFeatures\":8}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 484-feature input with 179 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1500\nComponents:\n - input (input) params={\"shape\":[1,484]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,484]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":484,\"outFeatures\":127}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":127,\"outFeatures\":208}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":208,\"outFeatures\":987}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":987,\"outFeatures\":179}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 103-dim input: encode down to a 65-dim bottleneck and decode back to 103. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1501\nComponents:\n - input (input) params={\"shape\":[1,103]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,103]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":103,\"outFeatures\":313}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":313,\"outFeatures\":65}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":65,\"outFeatures\":313}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":313,\"outFeatures\":103}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x52x52 image with 38 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1502\nComponents:\n - input (input) params={\"shape\":[1,3,52,52]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,52,52]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":60,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":60,\"outChannels\":9,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":9,\"outChannels\":33,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":33,\"outChannels\":18,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":18,\"outFeatures\":38}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 493-token sequences with 80 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1503\nComponents:\n - input (input) params={\"shape\":[1,493]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,493]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":24273,\"embeddingDim\":176}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":176,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":176,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":176,\"outFeatures\":80}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 203-token sequences with 76 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1504\nComponents:\n - input (input) params={\"shape\":[1,203]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,203]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":11275,\"embeddingDim\":264}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":264,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[264]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":264,\"outFeatures\":76}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (474) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-1505\nComponents:\n - input (input) params={\"shape\":[1,166]}\n - embed (embedding) params={\"numEmbeddings\":39083,\"embeddingDim\":474}\n - attn (multiHeadAttention) params={\"embedDim\":474,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":474,\"outFeatures\":52}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 1903-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1506\nComponents:\n - input (input) params={\"shape\":[1,65]}\n - fc1 (linear) params={\"inFeatures\":65,\"outFeatures\":1903}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":1903,\"outFeatures\":1903}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":1903,\"outFeatures\":1903}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":1903,\"outFeatures\":1903}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":1903,\"outFeatures\":2}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":65,\"outFeatures\":255}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":255,\"outFeatures\":255}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":255,\"outFeatures\":255}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":255,\"outFeatures\":255}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":255,\"outFeatures\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 228-feature, 45-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1507\nComponents:\n - input (input) params={\"shape\":[1,228]}\n - fc1 (linear) params={\"inFeatures\":228,\"outFeatures\":392}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":392,\"outFeatures\":217}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":217,\"outFeatures\":137}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":137,\"outFeatures\":409}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":409,\"outFeatures\":352}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":352,\"outFeatures\":45}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":392}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":217}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":137}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":409}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":352}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 95-feature user input and a 178-feature item input, each through its own 2-layer MLP tower ending at width 167, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1508\nComponents:\n - user_input (input) params={\"shape\":[1,95]}\n - item_input (input) params={\"shape\":[1,178]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,95]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,178]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":95,\"outFeatures\":167}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":167,\"outFeatures\":167}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":178,\"outFeatures\":167}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":167,\"outFeatures\":167}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":334,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (81-feature input, 5 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1509\nComponents:\n - input (input) params={\"shape\":[1,81]}\n - fc1 (linear) params={\"inFeatures\":81,\"outFeatures\":20}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":20,\"outFeatures\":20}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":20,\"outFeatures\":5}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":81,\"outFeatures\":1172}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1172,\"outFeatures\":1172}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1172,\"outFeatures\":5}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 187-feature input with 151 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1510\nComponents:\n - input (input) params={\"shape\":[1,187]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,187]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":187,\"outFeatures\":833}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":833,\"outFeatures\":782}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":782,\"outFeatures\":151}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 875-dim input: encode down to a 5-dim bottleneck and decode back to 875. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1511\nComponents:\n - input (input) params={\"shape\":[1,875]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,875]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":875,\"outFeatures\":708}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":708,\"outFeatures\":5}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":5,\"outFeatures\":708}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":708,\"outFeatures\":875}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x33x33 image with 22 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1512\nComponents:\n - input (input) params={\"shape\":[1,3,33,33]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,33,33]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":18,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":18,\"outChannels\":64,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":64,\"outFeatures\":22}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 277-token sequences with 35 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1513\nComponents:\n - input (input) params={\"shape\":[1,277]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,277]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":49234,\"embeddingDim\":114}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":114,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":114,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":114,\"outFeatures\":35}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 255-token sequences with 63 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1514\nComponents:\n - input (input) params={\"shape\":[1,255]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,255]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":42808,\"embeddingDim\":32}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":32,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[32]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":32,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[32]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":32,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[32]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":32,\"outFeatures\":63}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (186) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-1515\nComponents:\n - input (input) params={\"shape\":[1,185]}\n - embed (embedding) params={\"numEmbeddings\":9867,\"embeddingDim\":186}\n - attn (multiHeadAttention) params={\"embedDim\":186,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":186,\"outFeatures\":54}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3458-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1516\nComponents:\n - input (input) params={\"shape\":[1,70]}\n - fc1 (linear) params={\"inFeatures\":70,\"outFeatures\":3458}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3458,\"outFeatures\":3458}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3458,\"outFeatures\":3458}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3458,\"outFeatures\":3458}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3458,\"outFeatures\":9}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":70,\"outFeatures\":245}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":245,\"outFeatures\":245}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":245,\"outFeatures\":245}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":245,\"outFeatures\":245}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":245,\"outFeatures\":9}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 206-feature, 40-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1517\nComponents:\n - input (input) params={\"shape\":[1,206]}\n - fc1 (linear) params={\"inFeatures\":206,\"outFeatures\":480}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":480,\"outFeatures\":94}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":94,\"outFeatures\":438}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":438,\"outFeatures\":284}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":284,\"outFeatures\":333}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":333,\"outFeatures\":40}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":480}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":94}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":438}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":284}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":333}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 58-feature user input and a 226-feature item input, each through its own 2-layer MLP tower ending at width 291, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1518\nComponents:\n - user_input (input) params={\"shape\":[1,58]}\n - item_input (input) params={\"shape\":[1,226]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,58]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,226]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":58,\"outFeatures\":291}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":291,\"outFeatures\":291}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":226,\"outFeatures\":291}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":291,\"outFeatures\":291}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":582,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (71-feature input, 19 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1519\nComponents:\n - input (input) params={\"shape\":[1,71]}\n - fc1 (linear) params={\"inFeatures\":71,\"outFeatures\":22}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":22,\"outFeatures\":22}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":22,\"outFeatures\":19}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":71,\"outFeatures\":1386}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1386,\"outFeatures\":1386}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1386,\"outFeatures\":19}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 406-feature input with 152 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1520\nComponents:\n - input (input) params={\"shape\":[1,406]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,406]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":406,\"outFeatures\":274}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":274,\"outFeatures\":947}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":947,\"outFeatures\":121}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":121,\"outFeatures\":152}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 885-dim input: encode down to a 145-dim bottleneck and decode back to 885. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1521\nComponents:\n - input (input) params={\"shape\":[1,885]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,885]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":885,\"outFeatures\":690}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":690,\"outFeatures\":145}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":145,\"outFeatures\":690}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":690,\"outFeatures\":885}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x35x35 image with 70 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1522\nComponents:\n - input (input) params={\"shape\":[1,3,35,35]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,35,35]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":53,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":53,\"outChannels\":12,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":12,\"outFeatures\":70}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 398-token sequences with 93 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1523\nComponents:\n - input (input) params={\"shape\":[1,398]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,398]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":19691,\"embeddingDim\":148}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":148,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":148,\"outFeatures\":93}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 304-token sequences with 80 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1524\nComponents:\n - input (input) params={\"shape\":[1,304]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,304]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":33462,\"embeddingDim\":272}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":272,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[272]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":272,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[272]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":272,\"outFeatures\":80}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 2848-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1526\nComponents:\n - input (input) params={\"shape\":[1,251]}\n - fc1 (linear) params={\"inFeatures\":251,\"outFeatures\":2848}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2848,\"outFeatures\":2848}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2848,\"outFeatures\":2848}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":2848,\"outFeatures\":20}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":251,\"outFeatures\":353}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":353,\"outFeatures\":353}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":353,\"outFeatures\":353}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":353,\"outFeatures\":20}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 150-feature, 25-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1527\nComponents:\n - input (input) params={\"shape\":[1,150]}\n - fc1 (linear) params={\"inFeatures\":150,\"outFeatures\":245}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":245,\"outFeatures\":259}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":259,\"outFeatures\":434}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":434,\"outFeatures\":316}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":316,\"outFeatures\":322}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":322,\"outFeatures\":25}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":245}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":259}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":434}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":316}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":322}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 89-feature user input and a 189-feature item input, each through its own 2-layer MLP tower ending at width 374, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1528\nComponents:\n - user_input (input) params={\"shape\":[1,89]}\n - item_input (input) params={\"shape\":[1,189]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,89]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,189]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":89,\"outFeatures\":374}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":374,\"outFeatures\":374}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":189,\"outFeatures\":374}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":374,\"outFeatures\":374}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":748,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (62-feature input, 17 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1529\nComponents:\n - input (input) params={\"shape\":[1,62]}\n - fc1 (linear) params={\"inFeatures\":62,\"outFeatures\":20}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":20,\"outFeatures\":20}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":20,\"outFeatures\":17}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":62,\"outFeatures\":760}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":760,\"outFeatures\":760}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":760,\"outFeatures\":17}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 282-feature input with 10 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1530\nComponents:\n - input (input) params={\"shape\":[1,282]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,282]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":282,\"outFeatures\":506}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":506,\"outFeatures\":564}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":564,\"outFeatures\":536}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":536,\"outFeatures\":10}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1969-dim input: encode down to a 140-dim bottleneck and decode back to 1969. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1531\nComponents:\n - input (input) params={\"shape\":[1,1969]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1969]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1969,\"outFeatures\":889}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":889,\"outFeatures\":140}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":140,\"outFeatures\":889}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":889,\"outFeatures\":1969}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x30x30 image with 79 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1532\nComponents:\n - input (input) params={\"shape\":[1,3,30,30]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,30,30]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":8,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":8,\"outChannels\":13,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":13,\"outChannels\":48,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":48,\"outChannels\":53,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":53,\"outFeatures\":79}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 397-token sequences with 9 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1533\nComponents:\n - input (input) params={\"shape\":[1,397]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,397]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":15341,\"embeddingDim\":78}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":78,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":78,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":78,\"outFeatures\":9}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 352-token sequences with 55 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1534\nComponents:\n - input (input) params={\"shape\":[1,352]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,352]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":39657,\"embeddingDim\":368}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":368,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[368]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":368,\"outFeatures\":55}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 3793-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1536\nComponents:\n - input (input) params={\"shape\":[1,204]}\n - fc1 (linear) params={\"inFeatures\":204,\"outFeatures\":3793}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3793,\"outFeatures\":3793}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":3793,\"outFeatures\":38}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":204,\"outFeatures\":76}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":76,\"outFeatures\":76}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":76,\"outFeatures\":38}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 72-feature, 62-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1537\nComponents:\n - input (input) params={\"shape\":[1,72]}\n - fc1 (linear) params={\"inFeatures\":72,\"outFeatures\":426}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":426,\"outFeatures\":377}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":377,\"outFeatures\":479}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":479,\"outFeatures\":62}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":426}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":377}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":479}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 173-feature user input and a 215-feature item input, each through its own 2-layer MLP tower ending at width 376, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1538\nComponents:\n - user_input (input) params={\"shape\":[1,173]}\n - item_input (input) params={\"shape\":[1,215]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,173]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,215]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":173,\"outFeatures\":376}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":376,\"outFeatures\":376}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":215,\"outFeatures\":376}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":376,\"outFeatures\":376}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":752,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (97-feature input, 16 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1539\nComponents:\n - input (input) params={\"shape\":[1,97]}\n - fc1 (linear) params={\"inFeatures\":97,\"outFeatures\":23}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":23,\"outFeatures\":23}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":23,\"outFeatures\":16}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":97,\"outFeatures\":1025}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1025,\"outFeatures\":1025}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1025,\"outFeatures\":16}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 455-feature input with 75 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1540\nComponents:\n - input (input) params={\"shape\":[1,455]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,455]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":455,\"outFeatures\":147}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":147,\"outFeatures\":243}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":243,\"outFeatures\":670}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":670,\"outFeatures\":665}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":665,\"outFeatures\":919}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":919,\"outFeatures\":75}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1419-dim input: encode down to a 87-dim bottleneck and decode back to 1419. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1541\nComponents:\n - input (input) params={\"shape\":[1,1419]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1419]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1419,\"outFeatures\":236}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":236,\"outFeatures\":87}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":87,\"outFeatures\":236}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":236,\"outFeatures\":1419}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x52x52 image with 34 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1542\nComponents:\n - input (input) params={\"shape\":[1,3,52,52]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,52,52]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":18,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":18,\"outChannels\":44,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":44,\"outChannels\":16,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":16,\"outChannels\":8,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":8,\"outFeatures\":34}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 170-token sequences with 24 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1543\nComponents:\n - input (input) params={\"shape\":[1,170]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,170]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":9380,\"embeddingDim\":100}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":100,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":100,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":100,\"outFeatures\":24}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 346-token sequences with 31 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1544\nComponents:\n - input (input) params={\"shape\":[1,346]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,346]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":18897,\"embeddingDim\":232}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":232,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[232]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":232,\"outFeatures\":31}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 3183-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1546\nComponents:\n - input (input) params={\"shape\":[1,233]}\n - fc1 (linear) params={\"inFeatures\":233,\"outFeatures\":3183}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3183,\"outFeatures\":3183}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":3183,\"outFeatures\":32}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":233,\"outFeatures\":261}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":261,\"outFeatures\":261}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":261,\"outFeatures\":32}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 102-feature, 75-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1547\nComponents:\n - input (input) params={\"shape\":[1,102]}\n - fc1 (linear) params={\"inFeatures\":102,\"outFeatures\":243}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":243,\"outFeatures\":355}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":355,\"outFeatures\":75}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":243}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":355}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 159-feature user input and a 105-feature item input, each through its own 2-layer MLP tower ending at width 434, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1548\nComponents:\n - user_input (input) params={\"shape\":[1,159]}\n - item_input (input) params={\"shape\":[1,105]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,159]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,105]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":159,\"outFeatures\":434}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":434,\"outFeatures\":434}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":105,\"outFeatures\":434}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":434,\"outFeatures\":434}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":868,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (32-feature input, 38 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1549\nComponents:\n - input (input) params={\"shape\":[1,32]}\n - fc1 (linear) params={\"inFeatures\":32,\"outFeatures\":11}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":11,\"outFeatures\":11}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":11,\"outFeatures\":38}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":32,\"outFeatures\":1176}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1176,\"outFeatures\":1176}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1176,\"outFeatures\":38}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 161-feature input with 134 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1550\nComponents:\n - input (input) params={\"shape\":[1,161]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,161]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":161,\"outFeatures\":66}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":66,\"outFeatures\":84}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":84,\"outFeatures\":734}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":734,\"outFeatures\":287}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":287,\"outFeatures\":759}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":759,\"outFeatures\":134}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 123-dim input: encode down to a 236-dim bottleneck and decode back to 123. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1551\nComponents:\n - input (input) params={\"shape\":[1,123]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,123]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":123,\"outFeatures\":643}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":643,\"outFeatures\":236}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":236,\"outFeatures\":643}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":643,\"outFeatures\":123}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x31x31 image with 40 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1552\nComponents:\n - input (input) params={\"shape\":[1,3,31,31]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,31,31]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":8,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":8,\"outChannels\":9,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":9,\"outFeatures\":40}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 504-token sequences with 91 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1553\nComponents:\n - input (input) params={\"shape\":[1,504]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,504]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":15127,\"embeddingDim\":232}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":232,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":232,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":232,\"outFeatures\":91}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 307-token sequences with 3 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1554\nComponents:\n - input (input) params={\"shape\":[1,307]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,307]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":9811,\"embeddingDim\":176}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":176,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[176]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":176,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[176]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":176,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[176]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":176,\"outFeatures\":3}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 1884-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1556\nComponents:\n - input (input) params={\"shape\":[1,33]}\n - fc1 (linear) params={\"inFeatures\":33,\"outFeatures\":1884}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":1884,\"outFeatures\":1884}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":1884,\"outFeatures\":1884}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":1884,\"outFeatures\":1884}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":1884,\"outFeatures\":49}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":33,\"outFeatures\":378}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":378,\"outFeatures\":378}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":378,\"outFeatures\":378}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":378,\"outFeatures\":378}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":378,\"outFeatures\":49}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 165-feature, 31-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1557\nComponents:\n - input (input) params={\"shape\":[1,165]}\n - fc1 (linear) params={\"inFeatures\":165,\"outFeatures\":202}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":202,\"outFeatures\":369}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":369,\"outFeatures\":229}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":229,\"outFeatures\":245}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":245,\"outFeatures\":337}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":337,\"outFeatures\":31}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":202}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":369}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":229}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":245}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":337}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 152-feature user input and a 253-feature item input, each through its own 2-layer MLP tower ending at width 63, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1558\nComponents:\n - user_input (input) params={\"shape\":[1,152]}\n - item_input (input) params={\"shape\":[1,253]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,152]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,253]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":152,\"outFeatures\":63}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":63,\"outFeatures\":63}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":253,\"outFeatures\":63}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":63,\"outFeatures\":63}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":126,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (122-feature input, 19 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1559\nComponents:\n - input (input) params={\"shape\":[1,122]}\n - fc1 (linear) params={\"inFeatures\":122,\"outFeatures\":21}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":21,\"outFeatures\":21}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":21,\"outFeatures\":19}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":122,\"outFeatures\":1382}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1382,\"outFeatures\":1382}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1382,\"outFeatures\":19}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 271-feature input with 93 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1560\nComponents:\n - input (input) params={\"shape\":[1,271]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,271]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":271,\"outFeatures\":173}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":173,\"outFeatures\":893}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":893,\"outFeatures\":405}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":405,\"outFeatures\":93}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 455-dim input: encode down to a 59-dim bottleneck and decode back to 455. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1561\nComponents:\n - input (input) params={\"shape\":[1,455]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,455]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":455,\"outFeatures\":620}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":620,\"outFeatures\":59}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":59,\"outFeatures\":620}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":620,\"outFeatures\":455}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x37x37 image with 50 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1562\nComponents:\n - input (input) params={\"shape\":[1,3,37,37]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,37,37]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":45,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":45,\"outChannels\":18,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":18,\"outChannels\":20,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":20,\"outFeatures\":50}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 227-token sequences with 13 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1563\nComponents:\n - input (input) params={\"shape\":[1,227]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,227]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":18515,\"embeddingDim\":22}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":22,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":22,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":22,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":22,\"outFeatures\":13}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 431-token sequences with 90 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1564\nComponents:\n - input (input) params={\"shape\":[1,431]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,431]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":35589,\"embeddingDim\":176}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":176,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[176]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":176,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[176]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":176,\"outFeatures\":90}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (308) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-1565\nComponents:\n - input (input) params={\"shape\":[1,147]}\n - embed (embedding) params={\"numEmbeddings\":48782,\"embeddingDim\":308}\n - attn (multiHeadAttention) params={\"embedDim\":308,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":308,\"outFeatures\":7}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":4}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 2382-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1566\nComponents:\n - input (input) params={\"shape\":[1,220]}\n - fc1 (linear) params={\"inFeatures\":220,\"outFeatures\":2382}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2382,\"outFeatures\":2382}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2382,\"outFeatures\":2382}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":2382,\"outFeatures\":2382}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":2382,\"outFeatures\":39}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":220,\"outFeatures\":155}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":155,\"outFeatures\":155}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":155,\"outFeatures\":155}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":155,\"outFeatures\":155}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":155,\"outFeatures\":39}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 110-feature, 78-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1567\nComponents:\n - input (input) params={\"shape\":[1,110]}\n - fc1 (linear) params={\"inFeatures\":110,\"outFeatures\":223}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":223,\"outFeatures\":441}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":441,\"outFeatures\":134}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":134,\"outFeatures\":321}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":321,\"outFeatures\":380}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":380,\"outFeatures\":78}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":223}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":441}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":134}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":321}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":380}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 51-feature user input and a 189-feature item input, each through its own 2-layer MLP tower ending at width 508, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1568\nComponents:\n - user_input (input) params={\"shape\":[1,51]}\n - item_input (input) params={\"shape\":[1,189]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,51]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,189]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":51,\"outFeatures\":508}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":508,\"outFeatures\":508}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":189,\"outFeatures\":508}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":508,\"outFeatures\":508}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":1016,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (87-feature input, 38 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1569\nComponents:\n - input (input) params={\"shape\":[1,87]}\n - fc1 (linear) params={\"inFeatures\":87,\"outFeatures\":9}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":9,\"outFeatures\":9}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":9,\"outFeatures\":38}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":87,\"outFeatures\":1154}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1154,\"outFeatures\":1154}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1154,\"outFeatures\":38}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 493-feature input with 173 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1570\nComponents:\n - input (input) params={\"shape\":[1,493]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,493]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":493,\"outFeatures\":724}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":724,\"outFeatures\":875}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":875,\"outFeatures\":525}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":525,\"outFeatures\":967}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":967,\"outFeatures\":392}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":392,\"outFeatures\":1008}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":1008,\"outFeatures\":173}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 961-dim input: encode down to a 203-dim bottleneck and decode back to 961. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1571\nComponents:\n - input (input) params={\"shape\":[1,961]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,961]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":961,\"outFeatures\":539}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":539,\"outFeatures\":203}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":203,\"outFeatures\":539}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":539,\"outFeatures\":961}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x37x37 image with 31 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1572\nComponents:\n - input (input) params={\"shape\":[1,3,37,37]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,37,37]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":27,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":27,\"outChannels\":42,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":42,\"outChannels\":47,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":47,\"outFeatures\":31}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 275-token sequences with 91 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1573\nComponents:\n - input (input) params={\"shape\":[1,275]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,275]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":32546,\"embeddingDim\":140}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":140,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":140,\"outFeatures\":91}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 163-token sequences with 84 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1574\nComponents:\n - input (input) params={\"shape\":[1,163]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,163]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":20492,\"embeddingDim\":160}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":160,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[160]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":160,\"outFeatures\":84}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (490) is not divisible by numHeads (11). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-1575\nComponents:\n - input (input) params={\"shape\":[1,167]}\n - embed (embedding) params={\"numEmbeddings\":43617,\"embeddingDim\":490}\n - attn (multiHeadAttention) params={\"embedDim\":490,\"numHeads\":11}\n - head (linear) params={\"inFeatures\":490,\"outFeatures\":56}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 2770-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1576\nComponents:\n - input (input) params={\"shape\":[1,114]}\n - fc1 (linear) params={\"inFeatures\":114,\"outFeatures\":2770}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2770,\"outFeatures\":2770}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":2770,\"outFeatures\":34}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":114,\"outFeatures\":381}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":381,\"outFeatures\":381}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":381,\"outFeatures\":34}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 98-feature, 97-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1577\nComponents:\n - input (input) params={\"shape\":[1,98]}\n - fc1 (linear) params={\"inFeatures\":98,\"outFeatures\":433}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":433,\"outFeatures\":61}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":61,\"outFeatures\":457}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":457,\"outFeatures\":97}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":433}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":61}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":457}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 30-feature user input and a 118-feature item input, each through its own 2-layer MLP tower ending at width 200, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1578\nComponents:\n - user_input (input) params={\"shape\":[1,30]}\n - item_input (input) params={\"shape\":[1,118]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,30]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,118]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":30,\"outFeatures\":200}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":200,\"outFeatures\":200}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":118,\"outFeatures\":200}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":200,\"outFeatures\":200}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":400,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (97-feature input, 30 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1579\nComponents:\n - input (input) params={\"shape\":[1,97]}\n - fc1 (linear) params={\"inFeatures\":97,\"outFeatures\":19}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":19,\"outFeatures\":19}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":19,\"outFeatures\":30}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":97,\"outFeatures\":693}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":693,\"outFeatures\":693}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":693,\"outFeatures\":30}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 271-feature input with 198 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1580\nComponents:\n - input (input) params={\"shape\":[1,271]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,271]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":271,\"outFeatures\":441}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":441,\"outFeatures\":297}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":297,\"outFeatures\":278}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":278,\"outFeatures\":871}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":871,\"outFeatures\":436}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":436,\"outFeatures\":198}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1823-dim input: encode down to a 187-dim bottleneck and decode back to 1823. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1581\nComponents:\n - input (input) params={\"shape\":[1,1823]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1823]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1823,\"outFeatures\":374}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":374,\"outFeatures\":187}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":187,\"outFeatures\":374}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":374,\"outFeatures\":1823}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x30x30 image with 61 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1582\nComponents:\n - input (input) params={\"shape\":[1,3,30,30]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,30,30]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":60,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":60,\"outChannels\":33,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":33,\"outFeatures\":61}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 418-token sequences with 4 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1583\nComponents:\n - input (input) params={\"shape\":[1,418]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,418]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":8195,\"embeddingDim\":116}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":116,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":116,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":116,\"outFeatures\":4}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 68-token sequences with 40 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1584\nComponents:\n - input (input) params={\"shape\":[1,68]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,68]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":18110,\"embeddingDim\":624}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":624,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[624]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":624,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[624]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":624,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[624]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":624,\"outFeatures\":40}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 4082-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1586\nComponents:\n - input (input) params={\"shape\":[1,249]}\n - fc1 (linear) params={\"inFeatures\":249,\"outFeatures\":4082}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":4082,\"outFeatures\":4082}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":4082,\"outFeatures\":4082}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":4082,\"outFeatures\":44}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":249,\"outFeatures\":242}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":242,\"outFeatures\":242}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":242,\"outFeatures\":242}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":242,\"outFeatures\":44}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 98-feature, 3-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1587\nComponents:\n - input (input) params={\"shape\":[1,98]}\n - fc1 (linear) params={\"inFeatures\":98,\"outFeatures\":159}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":159,\"outFeatures\":196}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":196,\"outFeatures\":3}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":159}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":196}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 68-feature user input and a 92-feature item input, each through its own 2-layer MLP tower ending at width 184, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1588\nComponents:\n - user_input (input) params={\"shape\":[1,68]}\n - item_input (input) params={\"shape\":[1,92]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,68]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,92]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":68,\"outFeatures\":184}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":184,\"outFeatures\":184}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":92,\"outFeatures\":184}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":184,\"outFeatures\":184}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":368,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (96-feature input, 3 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1589\nComponents:\n - input (input) params={\"shape\":[1,96]}\n - fc1 (linear) params={\"inFeatures\":96,\"outFeatures\":6}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":6,\"outFeatures\":6}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":6,\"outFeatures\":3}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":96,\"outFeatures\":1147}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1147,\"outFeatures\":1147}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1147,\"outFeatures\":3}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 434-feature input with 52 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1590\nComponents:\n - input (input) params={\"shape\":[1,434]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,434]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":434,\"outFeatures\":1012}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1012,\"outFeatures\":451}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":451,\"outFeatures\":51}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":51,\"outFeatures\":52}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 450-dim input: encode down to a 111-dim bottleneck and decode back to 450. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1591\nComponents:\n - input (input) params={\"shape\":[1,450]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,450]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":450,\"outFeatures\":119}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":119,\"outFeatures\":111}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":111,\"outFeatures\":119}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":119,\"outFeatures\":450}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x38x38 image with 95 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1592\nComponents:\n - input (input) params={\"shape\":[1,3,38,38]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,38,38]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":26,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":26,\"outChannels\":43,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":43,\"outFeatures\":95}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 430-token sequences with 63 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1593\nComponents:\n - input (input) params={\"shape\":[1,430]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,430]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":30328,\"embeddingDim\":488}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":488,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":488,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":488,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":488,\"outFeatures\":63}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 424-token sequences with 22 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1594\nComponents:\n - input (input) params={\"shape\":[1,424]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,424]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":29018,\"embeddingDim\":240}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":240,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[240]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":240,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[240]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":240,\"outFeatures\":22}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (174) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-1595\nComponents:\n - input (input) params={\"shape\":[1,371]}\n - embed (embedding) params={\"numEmbeddings\":12318,\"embeddingDim\":174}\n - attn (multiHeadAttention) params={\"embedDim\":174,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":174,\"outFeatures\":67}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 4078-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1596\nComponents:\n - input (input) params={\"shape\":[1,146]}\n - fc1 (linear) params={\"inFeatures\":146,\"outFeatures\":4078}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":4078,\"outFeatures\":4078}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":4078,\"outFeatures\":23}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":146,\"outFeatures\":226}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":226,\"outFeatures\":226}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":226,\"outFeatures\":23}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 105-feature, 82-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1597\nComponents:\n - input (input) params={\"shape\":[1,105]}\n - fc1 (linear) params={\"inFeatures\":105,\"outFeatures\":200}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":200,\"outFeatures\":432}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":432,\"outFeatures\":401}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":401,\"outFeatures\":333}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":333,\"outFeatures\":82}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":200}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":432}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":401}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":333}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 36-feature user input and a 29-feature item input, each through its own 2-layer MLP tower ending at width 423, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1598\nComponents:\n - user_input (input) params={\"shape\":[1,36]}\n - item_input (input) params={\"shape\":[1,29]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,36]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,29]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":36,\"outFeatures\":423}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":423,\"outFeatures\":423}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":29,\"outFeatures\":423}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":423,\"outFeatures\":423}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":846,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (58-feature input, 43 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1599\nComponents:\n - input (input) params={\"shape\":[1,58]}\n - fc1 (linear) params={\"inFeatures\":58,\"outFeatures\":13}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":13,\"outFeatures\":13}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":13,\"outFeatures\":43}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":58,\"outFeatures\":1342}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1342,\"outFeatures\":1342}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1342,\"outFeatures\":43}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 374-feature input with 52 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1600\nComponents:\n - input (input) params={\"shape\":[1,374]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,374]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":374,\"outFeatures\":637}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":637,\"outFeatures\":886}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":886,\"outFeatures\":52}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1045-dim input: encode down to a 137-dim bottleneck and decode back to 1045. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1601\nComponents:\n - input (input) params={\"shape\":[1,1045]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1045]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1045,\"outFeatures\":1002}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":1002,\"outFeatures\":137}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":137,\"outFeatures\":1002}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":1002,\"outFeatures\":1045}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x46x46 image with 52 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1602\nComponents:\n - input (input) params={\"shape\":[1,3,46,46]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,46,46]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":53,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":53,\"outChannels\":8,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":8,\"outChannels\":57,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":57,\"outChannels\":33,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":33,\"outFeatures\":52}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 490-token sequences with 17 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1603\nComponents:\n - input (input) params={\"shape\":[1,490]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,490]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":16967,\"embeddingDim\":20}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":20,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":20,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":20,\"outFeatures\":17}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 492-token sequences with 63 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1604\nComponents:\n - input (input) params={\"shape\":[1,492]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,492]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":49821,\"embeddingDim\":416}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":416,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[416]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":416,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[416]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":416,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[416]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":416,\"outFeatures\":63}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 3335-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1606\nComponents:\n - input (input) params={\"shape\":[1,50]}\n - fc1 (linear) params={\"inFeatures\":50,\"outFeatures\":3335}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3335,\"outFeatures\":3335}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3335,\"outFeatures\":3335}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":3335,\"outFeatures\":44}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":50,\"outFeatures\":112}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":112,\"outFeatures\":112}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":112,\"outFeatures\":112}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":112,\"outFeatures\":44}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 253-feature, 58-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1607\nComponents:\n - input (input) params={\"shape\":[1,253]}\n - fc1 (linear) params={\"inFeatures\":253,\"outFeatures\":197}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":197,\"outFeatures\":453}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":453,\"outFeatures\":266}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":266,\"outFeatures\":58}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":197}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":453}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":266}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 208-feature user input and a 174-feature item input, each through its own 2-layer MLP tower ending at width 175, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1608\nComponents:\n - user_input (input) params={\"shape\":[1,208]}\n - item_input (input) params={\"shape\":[1,174]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,208]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,174]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":208,\"outFeatures\":175}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":175,\"outFeatures\":175}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":174,\"outFeatures\":175}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":175,\"outFeatures\":175}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":350,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 115-feature input with 22 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1610\nComponents:\n - input (input) params={\"shape\":[1,115]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,115]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":115,\"outFeatures\":613}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":613,\"outFeatures\":960}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":960,\"outFeatures\":22}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 979-dim input: encode down to a 54-dim bottleneck and decode back to 979. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1611\nComponents:\n - input (input) params={\"shape\":[1,979]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,979]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":979,\"outFeatures\":360}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":360,\"outFeatures\":54}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":54,\"outFeatures\":360}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":360,\"outFeatures\":979}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x28x28 image with 99 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1612\nComponents:\n - input (input) params={\"shape\":[1,3,28,28]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,28,28]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":44,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":44,\"outChannels\":17,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":17,\"outChannels\":62,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":62,\"outFeatures\":99}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 281-token sequences with 55 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1613\nComponents:\n - input (input) params={\"shape\":[1,281]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,281]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":13294,\"embeddingDim\":44}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":44,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":44,\"outFeatures\":55}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 106-token sequences with 23 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1614\nComponents:\n - input (input) params={\"shape\":[1,106]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,106]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":26672,\"embeddingDim\":72}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":72,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[72]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":72,\"outFeatures\":23}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 2620-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1616\nComponents:\n - input (input) params={\"shape\":[1,85]}\n - fc1 (linear) params={\"inFeatures\":85,\"outFeatures\":2620}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2620,\"outFeatures\":2620}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":2620,\"outFeatures\":31}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":85,\"outFeatures\":252}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":252,\"outFeatures\":252}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":252,\"outFeatures\":31}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 70-feature, 87-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1617\nComponents:\n - input (input) params={\"shape\":[1,70]}\n - fc1 (linear) params={\"inFeatures\":70,\"outFeatures\":330}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":330,\"outFeatures\":276}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":276,\"outFeatures\":330}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":330,\"outFeatures\":102}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":102,\"outFeatures\":351}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":351,\"outFeatures\":87}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":330}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":276}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":330}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":102}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":351}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 103-feature user input and a 248-feature item input, each through its own 2-layer MLP tower ending at width 319, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1618\nComponents:\n - user_input (input) params={\"shape\":[1,103]}\n - item_input (input) params={\"shape\":[1,248]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,103]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,248]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":103,\"outFeatures\":319}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":319,\"outFeatures\":319}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":248,\"outFeatures\":319}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":319,\"outFeatures\":319}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":638,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (88-feature input, 19 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1619\nComponents:\n - input (input) params={\"shape\":[1,88]}\n - fc1 (linear) params={\"inFeatures\":88,\"outFeatures\":17}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":17,\"outFeatures\":17}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":17,\"outFeatures\":19}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":88,\"outFeatures\":870}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":870,\"outFeatures\":870}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":870,\"outFeatures\":19}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 36-feature input with 199 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1620\nComponents:\n - input (input) params={\"shape\":[1,36]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,36]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":36,\"outFeatures\":530}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":530,\"outFeatures\":446}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":446,\"outFeatures\":777}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":777,\"outFeatures\":842}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":842,\"outFeatures\":199}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 594-dim input: encode down to a 5-dim bottleneck and decode back to 594. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1621\nComponents:\n - input (input) params={\"shape\":[1,594]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,594]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":594,\"outFeatures\":675}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":675,\"outFeatures\":5}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":5,\"outFeatures\":675}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":675,\"outFeatures\":594}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x58x58 image with 37 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1622\nComponents:\n - input (input) params={\"shape\":[1,3,58,58]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,58,58]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":17,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":17,\"outChannels\":62,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":62,\"outChannels\":52,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":52,\"outChannels\":14,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":14,\"outFeatures\":37}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 429-token sequences with 64 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1623\nComponents:\n - input (input) params={\"shape\":[1,429]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,429]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":37913,\"embeddingDim\":32}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":32,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":32,\"outFeatures\":64}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 179-token sequences with 58 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1624\nComponents:\n - input (input) params={\"shape\":[1,179]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,179]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":16692,\"embeddingDim\":80}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":80,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[80]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":80,\"outFeatures\":58}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 3376-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1626\nComponents:\n - input (input) params={\"shape\":[1,89]}\n - fc1 (linear) params={\"inFeatures\":89,\"outFeatures\":3376}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3376,\"outFeatures\":3376}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":3376,\"outFeatures\":40}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":89,\"outFeatures\":210}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":210,\"outFeatures\":210}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":210,\"outFeatures\":40}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 211-feature, 94-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1627\nComponents:\n - input (input) params={\"shape\":[1,211]}\n - fc1 (linear) params={\"inFeatures\":211,\"outFeatures\":441}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":441,\"outFeatures\":441}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":441,\"outFeatures\":94}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":441}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":441}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 247-feature user input and a 212-feature item input, each through its own 2-layer MLP tower ending at width 208, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1628\nComponents:\n - user_input (input) params={\"shape\":[1,247]}\n - item_input (input) params={\"shape\":[1,212]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,247]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,212]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":247,\"outFeatures\":208}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":208,\"outFeatures\":208}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":212,\"outFeatures\":208}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":208,\"outFeatures\":208}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":416,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (55-feature input, 40 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1629\nComponents:\n - input (input) params={\"shape\":[1,55]}\n - fc1 (linear) params={\"inFeatures\":55,\"outFeatures\":9}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":9,\"outFeatures\":9}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":9,\"outFeatures\":40}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":55,\"outFeatures\":1301}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1301,\"outFeatures\":1301}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1301,\"outFeatures\":40}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 21-feature input with 143 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1630\nComponents:\n - input (input) params={\"shape\":[1,21]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,21]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":21,\"outFeatures\":774}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":774,\"outFeatures\":355}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":355,\"outFeatures\":518}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":518,\"outFeatures\":444}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":444,\"outFeatures\":143}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 724-dim input: encode down to a 61-dim bottleneck and decode back to 724. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1631\nComponents:\n - input (input) params={\"shape\":[1,724]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,724]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":724,\"outFeatures\":187}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":187,\"outFeatures\":61}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":61,\"outFeatures\":187}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":187,\"outFeatures\":724}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x48x48 image with 45 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1632\nComponents:\n - input (input) params={\"shape\":[1,3,48,48]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,48,48]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":41,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":41,\"outChannels\":22,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":22,\"outChannels\":64,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":64,\"outChannels\":30,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":30,\"outFeatures\":45}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 214-token sequences with 42 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1633\nComponents:\n - input (input) params={\"shape\":[1,214]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,214]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":29725,\"embeddingDim\":312}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":312,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":312,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":312,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":312,\"outFeatures\":42}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 453-token sequences with 65 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1634\nComponents:\n - input (input) params={\"shape\":[1,453]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,453]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":18743,\"embeddingDim\":240}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":240,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[240]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":240,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[240]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":240,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[240]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":240,\"outFeatures\":65}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 2648-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1636\nComponents:\n - input (input) params={\"shape\":[1,177]}\n - fc1 (linear) params={\"inFeatures\":177,\"outFeatures\":2648}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2648,\"outFeatures\":2648}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":2648,\"outFeatures\":32}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":177,\"outFeatures\":301}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":301,\"outFeatures\":301}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":301,\"outFeatures\":32}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 121-feature, 28-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1637\nComponents:\n - input (input) params={\"shape\":[1,121]}\n - fc1 (linear) params={\"inFeatures\":121,\"outFeatures\":498}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":498,\"outFeatures\":278}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":278,\"outFeatures\":104}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":104,\"outFeatures\":482}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":482,\"outFeatures\":354}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":354,\"outFeatures\":28}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":498}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":278}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":104}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":482}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":354}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 116-feature user input and a 131-feature item input, each through its own 2-layer MLP tower ending at width 160, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1638\nComponents:\n - user_input (input) params={\"shape\":[1,116]}\n - item_input (input) params={\"shape\":[1,131]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,116]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,131]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":116,\"outFeatures\":160}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":160,\"outFeatures\":160}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":131,\"outFeatures\":160}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":160,\"outFeatures\":160}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":320,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (87-feature input, 19 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1639\nComponents:\n - input (input) params={\"shape\":[1,87]}\n - fc1 (linear) params={\"inFeatures\":87,\"outFeatures\":23}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":23,\"outFeatures\":23}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":23,\"outFeatures\":19}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":87,\"outFeatures\":1033}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1033,\"outFeatures\":1033}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1033,\"outFeatures\":19}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 93-feature input with 40 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1640\nComponents:\n - input (input) params={\"shape\":[1,93]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,93]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":93,\"outFeatures\":683}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":683,\"outFeatures\":35}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":35,\"outFeatures\":875}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":875,\"outFeatures\":614}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":614,\"outFeatures\":309}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":309,\"outFeatures\":40}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 865-dim input: encode down to a 24-dim bottleneck and decode back to 865. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1641\nComponents:\n - input (input) params={\"shape\":[1,865]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,865]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":865,\"outFeatures\":798}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":798,\"outFeatures\":24}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":24,\"outFeatures\":798}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":798,\"outFeatures\":865}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x29x29 image with 54 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1642\nComponents:\n - input (input) params={\"shape\":[1,3,29,29]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,29,29]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":59,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":59,\"outChannels\":62,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":62,\"outChannels\":19,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":19,\"outFeatures\":54}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 450-token sequences with 75 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1643\nComponents:\n - input (input) params={\"shape\":[1,450]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,450]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":36655,\"embeddingDim\":448}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":448,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":448,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":448,\"outFeatures\":75}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 362-token sequences with 50 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1644\nComponents:\n - input (input) params={\"shape\":[1,362]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,362]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":33119,\"embeddingDim\":256}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":256,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[256]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":256,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[256]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":256,\"outFeatures\":50}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (84) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-1645\nComponents:\n - input (input) params={\"shape\":[1,77]}\n - embed (embedding) params={\"numEmbeddings\":9880,\"embeddingDim\":84}\n - attn (multiHeadAttention) params={\"embedDim\":84,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":84,\"outFeatures\":97}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":4}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 1623-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1646\nComponents:\n - input (input) params={\"shape\":[1,157]}\n - fc1 (linear) params={\"inFeatures\":157,\"outFeatures\":1623}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":1623,\"outFeatures\":1623}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":1623,\"outFeatures\":28}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":157,\"outFeatures\":120}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":120,\"outFeatures\":120}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":120,\"outFeatures\":28}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 181-feature, 98-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1647\nComponents:\n - input (input) params={\"shape\":[1,181]}\n - fc1 (linear) params={\"inFeatures\":181,\"outFeatures\":293}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":293,\"outFeatures\":64}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":64,\"outFeatures\":134}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":134,\"outFeatures\":477}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":477,\"outFeatures\":275}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":275,\"outFeatures\":98}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":293}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":64}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":134}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":477}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":275}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 70-feature user input and a 129-feature item input, each through its own 2-layer MLP tower ending at width 384, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1648\nComponents:\n - user_input (input) params={\"shape\":[1,70]}\n - item_input (input) params={\"shape\":[1,129]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,70]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,129]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":70,\"outFeatures\":384}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":384,\"outFeatures\":384}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":129,\"outFeatures\":384}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":384,\"outFeatures\":384}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":768,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (34-feature input, 13 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1649\nComponents:\n - input (input) params={\"shape\":[1,34]}\n - fc1 (linear) params={\"inFeatures\":34,\"outFeatures\":5}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":5,\"outFeatures\":5}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":5,\"outFeatures\":13}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":34,\"outFeatures\":1330}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1330,\"outFeatures\":1330}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1330,\"outFeatures\":13}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 161-feature input with 59 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1650\nComponents:\n - input (input) params={\"shape\":[1,161]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,161]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":161,\"outFeatures\":135}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":135,\"outFeatures\":899}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":899,\"outFeatures\":386}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":386,\"outFeatures\":826}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":826,\"outFeatures\":59}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 840-dim input: encode down to a 149-dim bottleneck and decode back to 840. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1651\nComponents:\n - input (input) params={\"shape\":[1,840]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,840]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":840,\"outFeatures\":502}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":502,\"outFeatures\":149}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":149,\"outFeatures\":502}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":502,\"outFeatures\":840}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x34x34 image with 5 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1652\nComponents:\n - input (input) params={\"shape\":[1,3,34,34]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,34,34]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":14,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":14,\"outChannels\":40,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":40,\"outChannels\":40,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":40,\"outFeatures\":5}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 126-token sequences with 40 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1653\nComponents:\n - input (input) params={\"shape\":[1,126]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,126]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":30537,\"embeddingDim\":192}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":192,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":192,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":192,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":192,\"outFeatures\":40}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 128-token sequences with 13 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1654\nComponents:\n - input (input) params={\"shape\":[1,128]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,128]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":25680,\"embeddingDim\":180}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":180,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[180]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":180,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[180]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":180,\"outFeatures\":13}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 2855-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1656\nComponents:\n - input (input) params={\"shape\":[1,67]}\n - fc1 (linear) params={\"inFeatures\":67,\"outFeatures\":2855}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2855,\"outFeatures\":2855}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2855,\"outFeatures\":2855}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":2855,\"outFeatures\":2855}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":2855,\"outFeatures\":10}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":67,\"outFeatures\":162}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":162,\"outFeatures\":162}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":162,\"outFeatures\":162}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":162,\"outFeatures\":162}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":162,\"outFeatures\":10}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 89-feature, 5-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1657\nComponents:\n - input (input) params={\"shape\":[1,89]}\n - fc1 (linear) params={\"inFeatures\":89,\"outFeatures\":461}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":461,\"outFeatures\":305}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":305,\"outFeatures\":350}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":350,\"outFeatures\":242}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":242,\"outFeatures\":419}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":419,\"outFeatures\":5}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":461}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":305}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":350}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":242}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":419}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 152-feature user input and a 199-feature item input, each through its own 2-layer MLP tower ending at width 357, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1658\nComponents:\n - user_input (input) params={\"shape\":[1,152]}\n - item_input (input) params={\"shape\":[1,199]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,152]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,199]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":152,\"outFeatures\":357}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":357,\"outFeatures\":357}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":199,\"outFeatures\":357}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":357,\"outFeatures\":357}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":714,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (62-feature input, 7 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1659\nComponents:\n - input (input) params={\"shape\":[1,62]}\n - fc1 (linear) params={\"inFeatures\":62,\"outFeatures\":11}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":11,\"outFeatures\":11}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":11,\"outFeatures\":7}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":62,\"outFeatures\":1371}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1371,\"outFeatures\":1371}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1371,\"outFeatures\":7}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 316-feature input with 12 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1660\nComponents:\n - input (input) params={\"shape\":[1,316]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,316]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":316,\"outFeatures\":388}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":388,\"outFeatures\":423}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":423,\"outFeatures\":89}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":89,\"outFeatures\":881}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":881,\"outFeatures\":12}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1504-dim input: encode down to a 34-dim bottleneck and decode back to 1504. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1661\nComponents:\n - input (input) params={\"shape\":[1,1504]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1504]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1504,\"outFeatures\":177}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":177,\"outFeatures\":34}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":34,\"outFeatures\":177}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":177,\"outFeatures\":1504}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x44x44 image with 6 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1662\nComponents:\n - input (input) params={\"shape\":[1,3,44,44]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,44,44]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":51,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":51,\"outChannels\":28,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":28,\"outFeatures\":6}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 78-token sequences with 54 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1663\nComponents:\n - input (input) params={\"shape\":[1,78]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,78]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":41903,\"embeddingDim\":20}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":20,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":20,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":20,\"outFeatures\":54}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 128-token sequences with 76 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1664\nComponents:\n - input (input) params={\"shape\":[1,128]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,128]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":19113,\"embeddingDim\":224}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":224,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[224]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":224,\"outFeatures\":76}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 3036-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1666\nComponents:\n - input (input) params={\"shape\":[1,218]}\n - fc1 (linear) params={\"inFeatures\":218,\"outFeatures\":3036}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3036,\"outFeatures\":3036}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":3036,\"outFeatures\":3}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":218,\"outFeatures\":113}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":113,\"outFeatures\":113}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":113,\"outFeatures\":3}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 199-feature, 31-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1667\nComponents:\n - input (input) params={\"shape\":[1,199]}\n - fc1 (linear) params={\"inFeatures\":199,\"outFeatures\":171}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":171,\"outFeatures\":493}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":493,\"outFeatures\":451}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":451,\"outFeatures\":165}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":165,\"outFeatures\":31}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":171}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":493}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":451}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":165}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 59-feature user input and a 233-feature item input, each through its own 2-layer MLP tower ending at width 235, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1668\nComponents:\n - user_input (input) params={\"shape\":[1,59]}\n - item_input (input) params={\"shape\":[1,233]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,59]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,233]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":59,\"outFeatures\":235}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":235,\"outFeatures\":235}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":233,\"outFeatures\":235}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":235,\"outFeatures\":235}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":470,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (59-feature input, 44 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1669\nComponents:\n - input (input) params={\"shape\":[1,59]}\n - fc1 (linear) params={\"inFeatures\":59,\"outFeatures\":23}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":23,\"outFeatures\":23}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":23,\"outFeatures\":44}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":59,\"outFeatures\":716}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":716,\"outFeatures\":716}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":716,\"outFeatures\":44}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 39-feature input with 199 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1670\nComponents:\n - input (input) params={\"shape\":[1,39]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,39]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":39,\"outFeatures\":411}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":411,\"outFeatures\":369}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":369,\"outFeatures\":199}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1741-dim input: encode down to a 204-dim bottleneck and decode back to 1741. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1671\nComponents:\n - input (input) params={\"shape\":[1,1741]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1741]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1741,\"outFeatures\":568}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":568,\"outFeatures\":204}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":204,\"outFeatures\":568}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":568,\"outFeatures\":1741}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x64x64 image with 36 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1672\nComponents:\n - input (input) params={\"shape\":[1,3,64,64]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,64,64]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":53,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":53,\"outChannels\":29,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":29,\"outChannels\":34,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":34,\"outFeatures\":36}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 284-token sequences with 40 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1673\nComponents:\n - input (input) params={\"shape\":[1,284]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,284]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":13640,\"embeddingDim\":40}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":40,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":40,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":40,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":40,\"outFeatures\":40}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 407-token sequences with 79 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1674\nComponents:\n - input (input) params={\"shape\":[1,407]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,407]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":25135,\"embeddingDim\":224}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":224,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[224]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":224,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[224]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":224,\"outFeatures\":79}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 2671-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1676\nComponents:\n - input (input) params={\"shape\":[1,217]}\n - fc1 (linear) params={\"inFeatures\":217,\"outFeatures\":2671}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2671,\"outFeatures\":2671}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2671,\"outFeatures\":2671}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":2671,\"outFeatures\":26}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":217,\"outFeatures\":84}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":84,\"outFeatures\":84}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":84,\"outFeatures\":84}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":84,\"outFeatures\":26}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 138-feature, 85-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1677\nComponents:\n - input (input) params={\"shape\":[1,138]}\n - fc1 (linear) params={\"inFeatures\":138,\"outFeatures\":451}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":451,\"outFeatures\":99}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":99,\"outFeatures\":85}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":451}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":99}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 240-feature user input and a 245-feature item input, each through its own 2-layer MLP tower ending at width 82, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1678\nComponents:\n - user_input (input) params={\"shape\":[1,240]}\n - item_input (input) params={\"shape\":[1,245]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,240]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,245]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":240,\"outFeatures\":82}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":82,\"outFeatures\":82}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":245,\"outFeatures\":82}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":82,\"outFeatures\":82}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":164,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (55-feature input, 3 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1679\nComponents:\n - input (input) params={\"shape\":[1,55]}\n - fc1 (linear) params={\"inFeatures\":55,\"outFeatures\":22}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":22,\"outFeatures\":22}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":22,\"outFeatures\":3}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":55,\"outFeatures\":1310}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1310,\"outFeatures\":1310}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1310,\"outFeatures\":3}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 293-feature input with 4 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1680\nComponents:\n - input (input) params={\"shape\":[1,293]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,293]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":293,\"outFeatures\":151}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":151,\"outFeatures\":609}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":609,\"outFeatures\":31}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":31,\"outFeatures\":133}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":133,\"outFeatures\":471}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":471,\"outFeatures\":425}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":425,\"outFeatures\":4}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1709-dim input: encode down to a 102-dim bottleneck and decode back to 1709. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1681\nComponents:\n - input (input) params={\"shape\":[1,1709]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1709]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1709,\"outFeatures\":456}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":456,\"outFeatures\":102}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":102,\"outFeatures\":456}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":456,\"outFeatures\":1709}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x53x53 image with 37 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1682\nComponents:\n - input (input) params={\"shape\":[1,3,53,53]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,53,53]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":51,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":51,\"outChannels\":24,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":24,\"outChannels\":49,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":49,\"outFeatures\":37}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 489-token sequences with 34 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1683\nComponents:\n - input (input) params={\"shape\":[1,489]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,489]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":22822,\"embeddingDim\":104}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":104,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":104,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":104,\"outFeatures\":34}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 445-token sequences with 26 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1684\nComponents:\n - input (input) params={\"shape\":[1,445]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,445]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":24226,\"embeddingDim\":116}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":116,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[116]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":116,\"outFeatures\":26}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 2241-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1686\nComponents:\n - input (input) params={\"shape\":[1,32]}\n - fc1 (linear) params={\"inFeatures\":32,\"outFeatures\":2241}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2241,\"outFeatures\":2241}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2241,\"outFeatures\":2241}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":2241,\"outFeatures\":2241}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":2241,\"outFeatures\":35}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":32,\"outFeatures\":285}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":285,\"outFeatures\":285}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":285,\"outFeatures\":285}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":285,\"outFeatures\":285}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":285,\"outFeatures\":35}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 83-feature, 87-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1687\nComponents:\n - input (input) params={\"shape\":[1,83]}\n - fc1 (linear) params={\"inFeatures\":83,\"outFeatures\":155}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":155,\"outFeatures\":356}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":356,\"outFeatures\":87}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":155}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":356}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 254-feature user input and a 253-feature item input, each through its own 2-layer MLP tower ending at width 247, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1688\nComponents:\n - user_input (input) params={\"shape\":[1,254]}\n - item_input (input) params={\"shape\":[1,253]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,254]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,253]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":254,\"outFeatures\":247}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":247,\"outFeatures\":247}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":253,\"outFeatures\":247}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":247,\"outFeatures\":247}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":494,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (124-feature input, 12 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1689\nComponents:\n - input (input) params={\"shape\":[1,124]}\n - fc1 (linear) params={\"inFeatures\":124,\"outFeatures\":17}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":17,\"outFeatures\":17}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":17,\"outFeatures\":12}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":124,\"outFeatures\":663}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":663,\"outFeatures\":663}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":663,\"outFeatures\":12}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 227-feature input with 122 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1690\nComponents:\n - input (input) params={\"shape\":[1,227]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,227]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":227,\"outFeatures\":170}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":170,\"outFeatures\":899}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":899,\"outFeatures\":276}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":276,\"outFeatures\":122}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1498-dim input: encode down to a 230-dim bottleneck and decode back to 1498. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1691\nComponents:\n - input (input) params={\"shape\":[1,1498]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1498]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1498,\"outFeatures\":697}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":697,\"outFeatures\":230}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":230,\"outFeatures\":697}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":697,\"outFeatures\":1498}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x33x33 image with 87 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1692\nComponents:\n - input (input) params={\"shape\":[1,3,33,33]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,33,33]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":42,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":42,\"outChannels\":11,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":11,\"outChannels\":24,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":24,\"outFeatures\":87}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 80-token sequences with 68 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1693\nComponents:\n - input (input) params={\"shape\":[1,80]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,80]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":49098,\"embeddingDim\":320}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":320,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":320,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":320,\"outFeatures\":68}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 115-token sequences with 98 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1694\nComponents:\n - input (input) params={\"shape\":[1,115]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,115]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":27114,\"embeddingDim\":368}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":368,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[368]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":368,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[368]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":368,\"outFeatures\":98}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (78) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-1695\nComponents:\n - input (input) params={\"shape\":[1,318]}\n - embed (embedding) params={\"numEmbeddings\":32070,\"embeddingDim\":78}\n - attn (multiHeadAttention) params={\"embedDim\":78,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":78,\"outFeatures\":73}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 1745-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1696\nComponents:\n - input (input) params={\"shape\":[1,108]}\n - fc1 (linear) params={\"inFeatures\":108,\"outFeatures\":1745}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":1745,\"outFeatures\":1745}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":1745,\"outFeatures\":1745}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":1745,\"outFeatures\":1745}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":1745,\"outFeatures\":29}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":108,\"outFeatures\":373}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":373,\"outFeatures\":373}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":373,\"outFeatures\":373}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":373,\"outFeatures\":373}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":373,\"outFeatures\":29}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 217-feature, 41-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1697\nComponents:\n - input (input) params={\"shape\":[1,217]}\n - fc1 (linear) params={\"inFeatures\":217,\"outFeatures\":174}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":174,\"outFeatures\":243}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":243,\"outFeatures\":202}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":202,\"outFeatures\":261}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":261,\"outFeatures\":402}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":402,\"outFeatures\":41}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":174}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":243}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":202}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":261}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":402}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 103-feature user input and a 54-feature item input, each through its own 2-layer MLP tower ending at width 202, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1698\nComponents:\n - user_input (input) params={\"shape\":[1,103]}\n - item_input (input) params={\"shape\":[1,54]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,103]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,54]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":103,\"outFeatures\":202}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":202,\"outFeatures\":202}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":54,\"outFeatures\":202}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":202,\"outFeatures\":202}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":404,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (27-feature input, 8 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1699\nComponents:\n - input (input) params={\"shape\":[1,27]}\n - fc1 (linear) params={\"inFeatures\":27,\"outFeatures\":19}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":19,\"outFeatures\":19}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":19,\"outFeatures\":8}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":27,\"outFeatures\":665}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":665,\"outFeatures\":665}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":665,\"outFeatures\":8}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 319-feature input with 91 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1700\nComponents:\n - input (input) params={\"shape\":[1,319]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,319]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":319,\"outFeatures\":56}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":56,\"outFeatures\":756}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":756,\"outFeatures\":298}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":298,\"outFeatures\":876}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":876,\"outFeatures\":1006}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":1006,\"outFeatures\":91}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1729-dim input: encode down to a 129-dim bottleneck and decode back to 1729. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1701\nComponents:\n - input (input) params={\"shape\":[1,1729]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1729]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1729,\"outFeatures\":202}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":202,\"outFeatures\":129}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":129,\"outFeatures\":202}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":202,\"outFeatures\":1729}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x42x42 image with 66 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1702\nComponents:\n - input (input) params={\"shape\":[1,3,42,42]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,42,42]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":53,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":53,\"outChannels\":28,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":28,\"outChannels\":19,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":19,\"outFeatures\":66}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 405-token sequences with 18 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1703\nComponents:\n - input (input) params={\"shape\":[1,405]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,405]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":39069,\"embeddingDim\":30}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":30,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":30,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":30,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":30,\"outFeatures\":18}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 343-token sequences with 30 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1704\nComponents:\n - input (input) params={\"shape\":[1,343]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,343]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":18048,\"embeddingDim\":384}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":384,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[384]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":384,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[384]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":384,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[384]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":384,\"outFeatures\":30}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (318) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-1705\nComponents:\n - input (input) params={\"shape\":[1,82]}\n - embed (embedding) params={\"numEmbeddings\":40617,\"embeddingDim\":318}\n - attn (multiHeadAttention) params={\"embedDim\":318,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":318,\"outFeatures\":99}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 3966-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1706\nComponents:\n - input (input) params={\"shape\":[1,189]}\n - fc1 (linear) params={\"inFeatures\":189,\"outFeatures\":3966}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3966,\"outFeatures\":3966}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3966,\"outFeatures\":3966}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":3966,\"outFeatures\":44}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":189,\"outFeatures\":359}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":359,\"outFeatures\":359}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":359,\"outFeatures\":359}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":359,\"outFeatures\":44}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 38-feature, 55-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1707\nComponents:\n - input (input) params={\"shape\":[1,38]}\n - fc1 (linear) params={\"inFeatures\":38,\"outFeatures\":38}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":38,\"outFeatures\":280}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":280,\"outFeatures\":55}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":38}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":280}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 85-feature user input and a 86-feature item input, each through its own 2-layer MLP tower ending at width 159, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1708\nComponents:\n - user_input (input) params={\"shape\":[1,85]}\n - item_input (input) params={\"shape\":[1,86]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,85]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,86]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":85,\"outFeatures\":159}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":159,\"outFeatures\":159}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":86,\"outFeatures\":159}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":159,\"outFeatures\":159}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":318,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (19-feature input, 42 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1709\nComponents:\n - input (input) params={\"shape\":[1,19]}\n - fc1 (linear) params={\"inFeatures\":19,\"outFeatures\":5}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":5,\"outFeatures\":5}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":5,\"outFeatures\":42}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":19,\"outFeatures\":1295}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1295,\"outFeatures\":1295}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1295,\"outFeatures\":42}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 109-feature input with 35 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1710\nComponents:\n - input (input) params={\"shape\":[1,109]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,109]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":109,\"outFeatures\":912}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":912,\"outFeatures\":884}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":884,\"outFeatures\":870}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":870,\"outFeatures\":845}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":845,\"outFeatures\":35}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1306-dim input: encode down to a 103-dim bottleneck and decode back to 1306. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1711\nComponents:\n - input (input) params={\"shape\":[1,1306]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1306]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1306,\"outFeatures\":857}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":857,\"outFeatures\":103}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":103,\"outFeatures\":857}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":857,\"outFeatures\":1306}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x39x39 image with 91 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1712\nComponents:\n - input (input) params={\"shape\":[1,3,39,39]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,39,39]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":51,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":51,\"outChannels\":26,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":26,\"outFeatures\":91}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 43-token sequences with 44 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1713\nComponents:\n - input (input) params={\"shape\":[1,43]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,43]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":29686,\"embeddingDim\":140}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":140,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":140,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":140,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":140,\"outFeatures\":44}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 323-token sequences with 54 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1714\nComponents:\n - input (input) params={\"shape\":[1,323]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,323]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":48024,\"embeddingDim\":200}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":200,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[200]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":200,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[200]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":200,\"outFeatures\":54}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 2635-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1716\nComponents:\n - input (input) params={\"shape\":[1,48]}\n - fc1 (linear) params={\"inFeatures\":48,\"outFeatures\":2635}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2635,\"outFeatures\":2635}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2635,\"outFeatures\":2635}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":2635,\"outFeatures\":2635}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":2635,\"outFeatures\":43}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":48,\"outFeatures\":125}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":125,\"outFeatures\":125}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":125,\"outFeatures\":125}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":125,\"outFeatures\":125}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":125,\"outFeatures\":43}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 17-feature, 20-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1717\nComponents:\n - input (input) params={\"shape\":[1,17]}\n - fc1 (linear) params={\"inFeatures\":17,\"outFeatures\":99}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":99,\"outFeatures\":284}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":284,\"outFeatures\":125}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":125,\"outFeatures\":171}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":171,\"outFeatures\":20}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":99}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":284}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":125}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":171}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 81-feature user input and a 220-feature item input, each through its own 2-layer MLP tower ending at width 303, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1718\nComponents:\n - user_input (input) params={\"shape\":[1,81]}\n - item_input (input) params={\"shape\":[1,220]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,81]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,220]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":81,\"outFeatures\":303}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":303,\"outFeatures\":303}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":220,\"outFeatures\":303}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":303,\"outFeatures\":303}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":606,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (65-feature input, 6 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1719\nComponents:\n - input (input) params={\"shape\":[1,65]}\n - fc1 (linear) params={\"inFeatures\":65,\"outFeatures\":20}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":20,\"outFeatures\":20}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":20,\"outFeatures\":6}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":65,\"outFeatures\":1161}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1161,\"outFeatures\":1161}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1161,\"outFeatures\":6}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 39-feature input with 8 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1720\nComponents:\n - input (input) params={\"shape\":[1,39]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,39]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":39,\"outFeatures\":363}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":363,\"outFeatures\":453}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":453,\"outFeatures\":504}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":504,\"outFeatures\":346}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":346,\"outFeatures\":40}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":40,\"outFeatures\":8}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1732-dim input: encode down to a 133-dim bottleneck and decode back to 1732. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1721\nComponents:\n - input (input) params={\"shape\":[1,1732]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1732]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1732,\"outFeatures\":521}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":521,\"outFeatures\":133}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":133,\"outFeatures\":521}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":521,\"outFeatures\":1732}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x36x36 image with 25 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1722\nComponents:\n - input (input) params={\"shape\":[1,3,36,36]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,36,36]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":34,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":34,\"outChannels\":51,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":51,\"outChannels\":27,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":27,\"outChannels\":59,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":59,\"outFeatures\":25}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 315-token sequences with 78 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1723\nComponents:\n - input (input) params={\"shape\":[1,315]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,315]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":13649,\"embeddingDim\":416}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":416,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":416,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":416,\"outFeatures\":78}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 437-token sequences with 12 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1724\nComponents:\n - input (input) params={\"shape\":[1,437]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,437]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":26087,\"embeddingDim\":136}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":136,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[136]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":136,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[136]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":136,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[136]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":136,\"outFeatures\":12}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 3090-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1726\nComponents:\n - input (input) params={\"shape\":[1,192]}\n - fc1 (linear) params={\"inFeatures\":192,\"outFeatures\":3090}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3090,\"outFeatures\":3090}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":3090,\"outFeatures\":23}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":192,\"outFeatures\":142}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":142,\"outFeatures\":142}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":142,\"outFeatures\":23}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 60-feature, 60-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1727\nComponents:\n - input (input) params={\"shape\":[1,60]}\n - fc1 (linear) params={\"inFeatures\":60,\"outFeatures\":98}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":98,\"outFeatures\":235}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":235,\"outFeatures\":301}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":301,\"outFeatures\":38}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":38,\"outFeatures\":169}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":169,\"outFeatures\":60}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":98}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":235}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":301}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":38}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":169}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 183-feature user input and a 102-feature item input, each through its own 2-layer MLP tower ending at width 435, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1728\nComponents:\n - user_input (input) params={\"shape\":[1,183]}\n - item_input (input) params={\"shape\":[1,102]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,183]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,102]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":183,\"outFeatures\":435}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":435,\"outFeatures\":435}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":102,\"outFeatures\":435}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":435,\"outFeatures\":435}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":870,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (122-feature input, 44 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1729\nComponents:\n - input (input) params={\"shape\":[1,122]}\n - fc1 (linear) params={\"inFeatures\":122,\"outFeatures\":8}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":8,\"outFeatures\":8}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":8,\"outFeatures\":44}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":122,\"outFeatures\":1083}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1083,\"outFeatures\":1083}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1083,\"outFeatures\":44}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 232-feature input with 190 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1730\nComponents:\n - input (input) params={\"shape\":[1,232]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,232]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":232,\"outFeatures\":183}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":183,\"outFeatures\":138}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":138,\"outFeatures\":46}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":46,\"outFeatures\":904}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":904,\"outFeatures\":657}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":657,\"outFeatures\":841}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":841,\"outFeatures\":190}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 421-dim input: encode down to a 54-dim bottleneck and decode back to 421. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1731\nComponents:\n - input (input) params={\"shape\":[1,421]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,421]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":421,\"outFeatures\":840}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":840,\"outFeatures\":54}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":54,\"outFeatures\":840}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":840,\"outFeatures\":421}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x53x53 image with 26 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1732\nComponents:\n - input (input) params={\"shape\":[1,3,53,53]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,53,53]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":22,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":22,\"outChannels\":13,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":13,\"outChannels\":26,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":26,\"outChannels\":45,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":45,\"outFeatures\":26}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 279-token sequences with 83 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1733\nComponents:\n - input (input) params={\"shape\":[1,279]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,279]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":37606,\"embeddingDim\":126}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":126,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":126,\"outFeatures\":83}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 120-token sequences with 56 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1734\nComponents:\n - input (input) params={\"shape\":[1,120]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,120]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":29496,\"embeddingDim\":96}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":96,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[96]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":96,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[96]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":96,\"outFeatures\":56}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 2264-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1736\nComponents:\n - input (input) params={\"shape\":[1,34]}\n - fc1 (linear) params={\"inFeatures\":34,\"outFeatures\":2264}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2264,\"outFeatures\":2264}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2264,\"outFeatures\":2264}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":2264,\"outFeatures\":23}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":34,\"outFeatures\":135}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":135,\"outFeatures\":135}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":135,\"outFeatures\":135}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":135,\"outFeatures\":23}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 75-feature, 14-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1737\nComponents:\n - input (input) params={\"shape\":[1,75]}\n - fc1 (linear) params={\"inFeatures\":75,\"outFeatures\":196}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":196,\"outFeatures\":430}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":430,\"outFeatures\":249}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":249,\"outFeatures\":53}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":53,\"outFeatures\":14}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":196}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":430}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":249}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":53}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 224-feature user input and a 71-feature item input, each through its own 2-layer MLP tower ending at width 483, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1738\nComponents:\n - user_input (input) params={\"shape\":[1,224]}\n - item_input (input) params={\"shape\":[1,71]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,224]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,71]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":224,\"outFeatures\":483}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":483,\"outFeatures\":483}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":71,\"outFeatures\":483}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":483,\"outFeatures\":483}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":966,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (45-feature input, 50 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1739\nComponents:\n - input (input) params={\"shape\":[1,45]}\n - fc1 (linear) params={\"inFeatures\":45,\"outFeatures\":11}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":11,\"outFeatures\":11}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":11,\"outFeatures\":50}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":45,\"outFeatures\":1022}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1022,\"outFeatures\":1022}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1022,\"outFeatures\":50}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 479-feature input with 173 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1740\nComponents:\n - input (input) params={\"shape\":[1,479]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,479]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":479,\"outFeatures\":627}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":627,\"outFeatures\":162}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":162,\"outFeatures\":264}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":264,\"outFeatures\":419}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":419,\"outFeatures\":377}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":377,\"outFeatures\":455}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":455,\"outFeatures\":173}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1960-dim input: encode down to a 36-dim bottleneck and decode back to 1960. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1741\nComponents:\n - input (input) params={\"shape\":[1,1960]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1960]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1960,\"outFeatures\":170}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":170,\"outFeatures\":36}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":36,\"outFeatures\":170}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":170,\"outFeatures\":1960}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x54x54 image with 31 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1742\nComponents:\n - input (input) params={\"shape\":[1,3,54,54]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,54,54]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":33,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":33,\"outChannels\":15,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":15,\"outChannels\":12,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":12,\"outFeatures\":31}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 269-token sequences with 19 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1743\nComponents:\n - input (input) params={\"shape\":[1,269]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,269]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":9069,\"embeddingDim\":88}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":88,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":88,\"outFeatures\":19}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 36-token sequences with 97 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1744\nComponents:\n - input (input) params={\"shape\":[1,36]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,36]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":15477,\"embeddingDim\":176}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":176,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[176]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":176,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[176]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":176,\"outFeatures\":97}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3211-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1746\nComponents:\n - input (input) params={\"shape\":[1,246]}\n - fc1 (linear) params={\"inFeatures\":246,\"outFeatures\":3211}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3211,\"outFeatures\":3211}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3211,\"outFeatures\":3211}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3211,\"outFeatures\":3211}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3211,\"outFeatures\":11}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":246,\"outFeatures\":220}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":220,\"outFeatures\":220}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":220,\"outFeatures\":220}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":220,\"outFeatures\":220}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":220,\"outFeatures\":11}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 214-feature, 95-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1747\nComponents:\n - input (input) params={\"shape\":[1,214]}\n - fc1 (linear) params={\"inFeatures\":214,\"outFeatures\":414}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":414,\"outFeatures\":166}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":166,\"outFeatures\":66}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":66,\"outFeatures\":95}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":414}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":166}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":66}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 176-feature user input and a 77-feature item input, each through its own 2-layer MLP tower ending at width 499, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1748\nComponents:\n - user_input (input) params={\"shape\":[1,176]}\n - item_input (input) params={\"shape\":[1,77]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,176]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,77]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":176,\"outFeatures\":499}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":499,\"outFeatures\":499}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":77,\"outFeatures\":499}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":499,\"outFeatures\":499}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":998,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (20-feature input, 34 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1749\nComponents:\n - input (input) params={\"shape\":[1,20]}\n - fc1 (linear) params={\"inFeatures\":20,\"outFeatures\":6}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":6,\"outFeatures\":6}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":6,\"outFeatures\":34}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":20,\"outFeatures\":755}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":755,\"outFeatures\":755}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":755,\"outFeatures\":34}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 445-feature input with 188 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1750\nComponents:\n - input (input) params={\"shape\":[1,445]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,445]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":445,\"outFeatures\":750}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":750,\"outFeatures\":256}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":256,\"outFeatures\":188}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 316-dim input: encode down to a 95-dim bottleneck and decode back to 316. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1751\nComponents:\n - input (input) params={\"shape\":[1,316]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,316]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":316,\"outFeatures\":1016}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":1016,\"outFeatures\":95}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":95,\"outFeatures\":1016}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":1016,\"outFeatures\":316}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x37x37 image with 35 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1752\nComponents:\n - input (input) params={\"shape\":[1,3,37,37]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,37,37]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":55,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":55,\"outChannels\":25,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":25,\"outChannels\":56,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":56,\"outChannels\":29,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":29,\"outFeatures\":35}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 94-token sequences with 22 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1753\nComponents:\n - input (input) params={\"shape\":[1,94]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,94]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":17238,\"embeddingDim\":288}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":288,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":288,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":288,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":288,\"outFeatures\":22}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 69-token sequences with 81 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1754\nComponents:\n - input (input) params={\"shape\":[1,69]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,69]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":42994,\"embeddingDim\":560}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":560,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[560]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":560,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[560]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":560,\"outFeatures\":81}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (216) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-1755\nComponents:\n - input (input) params={\"shape\":[1,183]}\n - embed (embedding) params={\"numEmbeddings\":37138,\"embeddingDim\":216}\n - attn (multiHeadAttention) params={\"embedDim\":216,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":216,\"outFeatures\":33}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":8}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 3561-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1756\nComponents:\n - input (input) params={\"shape\":[1,165]}\n - fc1 (linear) params={\"inFeatures\":165,\"outFeatures\":3561}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3561,\"outFeatures\":3561}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3561,\"outFeatures\":3561}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":3561,\"outFeatures\":9}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":165,\"outFeatures\":237}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":237,\"outFeatures\":237}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":237,\"outFeatures\":237}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":237,\"outFeatures\":9}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 130-feature, 13-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1757\nComponents:\n - input (input) params={\"shape\":[1,130]}\n - fc1 (linear) params={\"inFeatures\":130,\"outFeatures\":97}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":97,\"outFeatures\":75}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":75,\"outFeatures\":44}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":44,\"outFeatures\":13}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":97}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":75}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":44}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 228-feature user input and a 85-feature item input, each through its own 2-layer MLP tower ending at width 478, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1758\nComponents:\n - user_input (input) params={\"shape\":[1,228]}\n - item_input (input) params={\"shape\":[1,85]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,228]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,85]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":228,\"outFeatures\":478}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":478,\"outFeatures\":478}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":85,\"outFeatures\":478}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":478,\"outFeatures\":478}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":956,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (18-feature input, 40 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1759\nComponents:\n - input (input) params={\"shape\":[1,18]}\n - fc1 (linear) params={\"inFeatures\":18,\"outFeatures\":11}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":11,\"outFeatures\":11}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":11,\"outFeatures\":40}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":18,\"outFeatures\":979}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":979,\"outFeatures\":979}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":979,\"outFeatures\":40}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 335-feature input with 90 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1760\nComponents:\n - input (input) params={\"shape\":[1,335]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,335]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":335,\"outFeatures\":800}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":800,\"outFeatures\":415}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":415,\"outFeatures\":90}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1609-dim input: encode down to a 108-dim bottleneck and decode back to 1609. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1761\nComponents:\n - input (input) params={\"shape\":[1,1609]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1609]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1609,\"outFeatures\":342}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":342,\"outFeatures\":108}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":108,\"outFeatures\":342}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":342,\"outFeatures\":1609}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x63x63 image with 17 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1762\nComponents:\n - input (input) params={\"shape\":[1,3,63,63]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,63,63]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":37,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":37,\"outChannels\":47,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":47,\"outFeatures\":17}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 77-token sequences with 91 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1763\nComponents:\n - input (input) params={\"shape\":[1,77]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,77]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":37315,\"embeddingDim\":448}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":448,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":448,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":448,\"outFeatures\":91}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 227-token sequences with 34 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1764\nComponents:\n - input (input) params={\"shape\":[1,227]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,227]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":38036,\"embeddingDim\":288}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":288,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[288]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":288,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[288]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":288,\"outFeatures\":34}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (208) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-1765\nComponents:\n - input (input) params={\"shape\":[1,295]}\n - embed (embedding) params={\"numEmbeddings\":40811,\"embeddingDim\":208}\n - attn (multiHeadAttention) params={\"embedDim\":208,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":208,\"outFeatures\":79}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":16}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 2861-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1766\nComponents:\n - input (input) params={\"shape\":[1,236]}\n - fc1 (linear) params={\"inFeatures\":236,\"outFeatures\":2861}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2861,\"outFeatures\":2861}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":2861,\"outFeatures\":9}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":236,\"outFeatures\":319}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":319,\"outFeatures\":319}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":319,\"outFeatures\":9}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 241-feature, 7-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1767\nComponents:\n - input (input) params={\"shape\":[1,241]}\n - fc1 (linear) params={\"inFeatures\":241,\"outFeatures\":371}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":371,\"outFeatures\":353}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":353,\"outFeatures\":185}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":185,\"outFeatures\":180}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":180,\"outFeatures\":7}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":371}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":353}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":185}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":180}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 182-feature user input and a 144-feature item input, each through its own 2-layer MLP tower ending at width 266, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1768\nComponents:\n - user_input (input) params={\"shape\":[1,182]}\n - item_input (input) params={\"shape\":[1,144]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,182]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,144]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":182,\"outFeatures\":266}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":266,\"outFeatures\":266}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":144,\"outFeatures\":266}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":266,\"outFeatures\":266}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":532,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (47-feature input, 35 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1769\nComponents:\n - input (input) params={\"shape\":[1,47]}\n - fc1 (linear) params={\"inFeatures\":47,\"outFeatures\":5}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":5,\"outFeatures\":5}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":5,\"outFeatures\":35}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":47,\"outFeatures\":1113}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1113,\"outFeatures\":1113}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1113,\"outFeatures\":35}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 192-feature input with 37 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1770\nComponents:\n - input (input) params={\"shape\":[1,192]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,192]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":192,\"outFeatures\":72}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":72,\"outFeatures\":683}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":683,\"outFeatures\":288}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":288,\"outFeatures\":128}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":128,\"outFeatures\":800}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":800,\"outFeatures\":37}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1861-dim input: encode down to a 183-dim bottleneck and decode back to 1861. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1771\nComponents:\n - input (input) params={\"shape\":[1,1861]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1861]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1861,\"outFeatures\":710}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":710,\"outFeatures\":183}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":183,\"outFeatures\":710}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":710,\"outFeatures\":1861}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x49x49 image with 16 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1772\nComponents:\n - input (input) params={\"shape\":[1,3,49,49]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,49,49]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":38,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":38,\"outChannels\":55,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":55,\"outChannels\":20,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":20,\"outFeatures\":16}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 346-token sequences with 6 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1773\nComponents:\n - input (input) params={\"shape\":[1,346]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,346]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":19104,\"embeddingDim\":56}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":56,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":56,\"outFeatures\":6}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 210-token sequences with 77 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1774\nComponents:\n - input (input) params={\"shape\":[1,210]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,210]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":8691,\"embeddingDim\":52}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":52,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[52]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":52,\"outFeatures\":77}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (280) is not divisible by numHeads (11). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-1775\nComponents:\n - input (input) params={\"shape\":[1,158]}\n - embed (embedding) params={\"numEmbeddings\":12799,\"embeddingDim\":280}\n - attn (multiHeadAttention) params={\"embedDim\":280,\"numHeads\":11}\n - head (linear) params={\"inFeatures\":280,\"outFeatures\":26}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":8}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 3260-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1776\nComponents:\n - input (input) params={\"shape\":[1,66]}\n - fc1 (linear) params={\"inFeatures\":66,\"outFeatures\":3260}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3260,\"outFeatures\":3260}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":3260,\"outFeatures\":6}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":66,\"outFeatures\":361}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":361,\"outFeatures\":361}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":361,\"outFeatures\":6}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 159-feature, 20-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1777\nComponents:\n - input (input) params={\"shape\":[1,159]}\n - fc1 (linear) params={\"inFeatures\":159,\"outFeatures\":158}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":158,\"outFeatures\":190}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":190,\"outFeatures\":245}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":245,\"outFeatures\":203}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":203,\"outFeatures\":20}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":158}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":190}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":245}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":203}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 243-feature user input and a 248-feature item input, each through its own 2-layer MLP tower ending at width 190, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1778\nComponents:\n - user_input (input) params={\"shape\":[1,243]}\n - item_input (input) params={\"shape\":[1,248]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,243]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,248]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":243,\"outFeatures\":190}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":190,\"outFeatures\":190}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":248,\"outFeatures\":190}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":190,\"outFeatures\":190}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":380,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (85-feature input, 10 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1779\nComponents:\n - input (input) params={\"shape\":[1,85]}\n - fc1 (linear) params={\"inFeatures\":85,\"outFeatures\":4}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":4,\"outFeatures\":4}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":4,\"outFeatures\":10}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":85,\"outFeatures\":949}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":949,\"outFeatures\":949}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":949,\"outFeatures\":10}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 458-feature input with 114 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1780\nComponents:\n - input (input) params={\"shape\":[1,458]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,458]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":458,\"outFeatures\":267}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":267,\"outFeatures\":81}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":81,\"outFeatures\":470}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":470,\"outFeatures\":114}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1253-dim input: encode down to a 55-dim bottleneck and decode back to 1253. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1781\nComponents:\n - input (input) params={\"shape\":[1,1253]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1253]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1253,\"outFeatures\":553}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":553,\"outFeatures\":55}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":55,\"outFeatures\":553}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":553,\"outFeatures\":1253}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x61x61 image with 81 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1782\nComponents:\n - input (input) params={\"shape\":[1,3,61,61]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,61,61]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":58,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":58,\"outChannels\":64,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":64,\"outChannels\":11,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":11,\"outChannels\":47,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":47,\"outFeatures\":81}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 360-token sequences with 31 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1783\nComponents:\n - input (input) params={\"shape\":[1,360]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,360]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":32660,\"embeddingDim\":120}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":120,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":120,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":120,\"outFeatures\":31}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 110-token sequences with 55 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1784\nComponents:\n - input (input) params={\"shape\":[1,110]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,110]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":16238,\"embeddingDim\":264}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":264,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[264]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":264,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[264]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":264,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[264]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":264,\"outFeatures\":55}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3130-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1786\nComponents:\n - input (input) params={\"shape\":[1,220]}\n - fc1 (linear) params={\"inFeatures\":220,\"outFeatures\":3130}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3130,\"outFeatures\":3130}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3130,\"outFeatures\":3130}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3130,\"outFeatures\":3130}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3130,\"outFeatures\":38}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":220,\"outFeatures\":292}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":292,\"outFeatures\":292}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":292,\"outFeatures\":292}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":292,\"outFeatures\":292}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":292,\"outFeatures\":38}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 224-feature, 27-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1787\nComponents:\n - input (input) params={\"shape\":[1,224]}\n - fc1 (linear) params={\"inFeatures\":224,\"outFeatures\":205}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":205,\"outFeatures\":348}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":348,\"outFeatures\":40}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":40,\"outFeatures\":310}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":310,\"outFeatures\":321}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":321,\"outFeatures\":27}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":205}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":348}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":40}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":310}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":321}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 132-feature user input and a 91-feature item input, each through its own 2-layer MLP tower ending at width 273, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1788\nComponents:\n - user_input (input) params={\"shape\":[1,132]}\n - item_input (input) params={\"shape\":[1,91]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,132]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,91]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":132,\"outFeatures\":273}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":273,\"outFeatures\":273}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":91,\"outFeatures\":273}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":273,\"outFeatures\":273}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":546,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (87-feature input, 15 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1789\nComponents:\n - input (input) params={\"shape\":[1,87]}\n - fc1 (linear) params={\"inFeatures\":87,\"outFeatures\":14}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":14,\"outFeatures\":14}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":14,\"outFeatures\":15}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":87,\"outFeatures\":1236}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1236,\"outFeatures\":1236}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1236,\"outFeatures\":15}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 104-feature input with 18 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1790\nComponents:\n - input (input) params={\"shape\":[1,104]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,104]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":104,\"outFeatures\":686}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":686,\"outFeatures\":733}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":733,\"outFeatures\":791}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":791,\"outFeatures\":18}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 2007-dim input: encode down to a 148-dim bottleneck and decode back to 2007. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1791\nComponents:\n - input (input) params={\"shape\":[1,2007]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,2007]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":2007,\"outFeatures\":509}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":509,\"outFeatures\":148}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":148,\"outFeatures\":509}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":509,\"outFeatures\":2007}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x60x60 image with 72 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1792\nComponents:\n - input (input) params={\"shape\":[1,3,60,60]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,60,60]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":48,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":48,\"outChannels\":21,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":21,\"outChannels\":58,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":58,\"outChannels\":27,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":27,\"outFeatures\":72}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 427-token sequences with 68 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1793\nComponents:\n - input (input) params={\"shape\":[1,427]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,427]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":48033,\"embeddingDim\":76}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":76,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":76,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":76,\"outFeatures\":68}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 227-token sequences with 3 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1794\nComponents:\n - input (input) params={\"shape\":[1,227]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,227]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":31780,\"embeddingDim\":400}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":400,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[400]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":400,\"outFeatures\":3}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (294) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-1795\nComponents:\n - input (input) params={\"shape\":[1,269]}\n - embed (embedding) params={\"numEmbeddings\":48220,\"embeddingDim\":294}\n - attn (multiHeadAttention) params={\"embedDim\":294,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":294,\"outFeatures\":7}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3655-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1796\nComponents:\n - input (input) params={\"shape\":[1,85]}\n - fc1 (linear) params={\"inFeatures\":85,\"outFeatures\":3655}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3655,\"outFeatures\":3655}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3655,\"outFeatures\":3655}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3655,\"outFeatures\":3655}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3655,\"outFeatures\":37}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":85,\"outFeatures\":175}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":175,\"outFeatures\":175}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":175,\"outFeatures\":175}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":175,\"outFeatures\":175}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":175,\"outFeatures\":37}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 123-feature, 41-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1797\nComponents:\n - input (input) params={\"shape\":[1,123]}\n - fc1 (linear) params={\"inFeatures\":123,\"outFeatures\":115}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":115,\"outFeatures\":397}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":397,\"outFeatures\":41}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":115}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":397}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 204-feature user input and a 74-feature item input, each through its own 2-layer MLP tower ending at width 33, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1798\nComponents:\n - user_input (input) params={\"shape\":[1,204]}\n - item_input (input) params={\"shape\":[1,74]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,204]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,74]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":204,\"outFeatures\":33}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":33,\"outFeatures\":33}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":74,\"outFeatures\":33}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":33,\"outFeatures\":33}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":66,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (25-feature input, 17 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1799\nComponents:\n - input (input) params={\"shape\":[1,25]}\n - fc1 (linear) params={\"inFeatures\":25,\"outFeatures\":23}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":23,\"outFeatures\":23}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":23,\"outFeatures\":17}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":25,\"outFeatures\":798}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":798,\"outFeatures\":798}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":798,\"outFeatures\":17}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 244-feature input with 25 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1800\nComponents:\n - input (input) params={\"shape\":[1,244]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,244]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":244,\"outFeatures\":220}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":220,\"outFeatures\":188}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":188,\"outFeatures\":25}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1801-dim input: encode down to a 245-dim bottleneck and decode back to 1801. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1801\nComponents:\n - input (input) params={\"shape\":[1,1801]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1801]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1801,\"outFeatures\":425}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":425,\"outFeatures\":245}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":245,\"outFeatures\":425}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":425,\"outFeatures\":1801}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x40x40 image with 87 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1802\nComponents:\n - input (input) params={\"shape\":[1,3,40,40]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,40,40]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":24,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":24,\"outChannels\":12,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":12,\"outChannels\":18,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":18,\"outFeatures\":87}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 486-token sequences with 21 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1803\nComponents:\n - input (input) params={\"shape\":[1,486]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,486]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":36454,\"embeddingDim\":120}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":120,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":120,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":120,\"outFeatures\":21}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 276-token sequences with 25 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1804\nComponents:\n - input (input) params={\"shape\":[1,276]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,276]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":46486,\"embeddingDim\":704}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":704,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[704]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":704,\"outFeatures\":25}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 1747-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1806\nComponents:\n - input (input) params={\"shape\":[1,255]}\n - fc1 (linear) params={\"inFeatures\":255,\"outFeatures\":1747}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":1747,\"outFeatures\":1747}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":1747,\"outFeatures\":19}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":255,\"outFeatures\":126}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":126,\"outFeatures\":126}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":126,\"outFeatures\":19}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 49-feature, 8-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1807\nComponents:\n - input (input) params={\"shape\":[1,49]}\n - fc1 (linear) params={\"inFeatures\":49,\"outFeatures\":263}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":263,\"outFeatures\":293}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":293,\"outFeatures\":305}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":305,\"outFeatures\":165}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":165,\"outFeatures\":179}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":179,\"outFeatures\":8}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":263}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":293}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":305}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":165}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":179}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 253-feature user input and a 84-feature item input, each through its own 2-layer MLP tower ending at width 405, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1808\nComponents:\n - user_input (input) params={\"shape\":[1,253]}\n - item_input (input) params={\"shape\":[1,84]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,253]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,84]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":253,\"outFeatures\":405}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":405,\"outFeatures\":405}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":84,\"outFeatures\":405}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":405,\"outFeatures\":405}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":810,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (91-feature input, 43 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1809\nComponents:\n - input (input) params={\"shape\":[1,91]}\n - fc1 (linear) params={\"inFeatures\":91,\"outFeatures\":22}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":22,\"outFeatures\":22}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":22,\"outFeatures\":43}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":91,\"outFeatures\":1213}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1213,\"outFeatures\":1213}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1213,\"outFeatures\":43}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 442-feature input with 172 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1810\nComponents:\n - input (input) params={\"shape\":[1,442]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,442]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":442,\"outFeatures\":676}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":676,\"outFeatures\":855}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":855,\"outFeatures\":224}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":224,\"outFeatures\":172}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 985-dim input: encode down to a 49-dim bottleneck and decode back to 985. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1811\nComponents:\n - input (input) params={\"shape\":[1,985]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,985]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":985,\"outFeatures\":484}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":484,\"outFeatures\":49}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":49,\"outFeatures\":484}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":484,\"outFeatures\":985}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x63x63 image with 47 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1812\nComponents:\n - input (input) params={\"shape\":[1,3,63,63]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,63,63]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":23,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":23,\"outChannels\":38,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":38,\"outChannels\":54,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":54,\"outFeatures\":47}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 228-token sequences with 29 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1813\nComponents:\n - input (input) params={\"shape\":[1,228]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,228]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":30959,\"embeddingDim\":200}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":200,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":200,\"outFeatures\":29}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 395-token sequences with 23 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1814\nComponents:\n - input (input) params={\"shape\":[1,395]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,395]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":14274,\"embeddingDim\":336}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":336,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[336]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":336,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[336]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":336,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[336]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":336,\"outFeatures\":23}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 4079-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1816\nComponents:\n - input (input) params={\"shape\":[1,159]}\n - fc1 (linear) params={\"inFeatures\":159,\"outFeatures\":4079}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":4079,\"outFeatures\":4079}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":4079,\"outFeatures\":4079}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":4079,\"outFeatures\":4079}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":4079,\"outFeatures\":8}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":159,\"outFeatures\":275}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":275,\"outFeatures\":275}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":275,\"outFeatures\":275}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":275,\"outFeatures\":275}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":275,\"outFeatures\":8}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 126-feature, 39-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1817\nComponents:\n - input (input) params={\"shape\":[1,126]}\n - fc1 (linear) params={\"inFeatures\":126,\"outFeatures\":67}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":67,\"outFeatures\":49}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":49,\"outFeatures\":138}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":138,\"outFeatures\":39}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":67}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":49}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":138}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 22-feature user input and a 254-feature item input, each through its own 2-layer MLP tower ending at width 373, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1818\nComponents:\n - user_input (input) params={\"shape\":[1,22]}\n - item_input (input) params={\"shape\":[1,254]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,22]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,254]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":22,\"outFeatures\":373}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":373,\"outFeatures\":373}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":254,\"outFeatures\":373}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":373,\"outFeatures\":373}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":746,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (47-feature input, 21 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1819\nComponents:\n - input (input) params={\"shape\":[1,47]}\n - fc1 (linear) params={\"inFeatures\":47,\"outFeatures\":10}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":10,\"outFeatures\":10}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":10,\"outFeatures\":21}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":47,\"outFeatures\":1013}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1013,\"outFeatures\":1013}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1013,\"outFeatures\":21}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 296-feature input with 69 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1820\nComponents:\n - input (input) params={\"shape\":[1,296]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,296]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":296,\"outFeatures\":615}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":615,\"outFeatures\":243}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":243,\"outFeatures\":294}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":294,\"outFeatures\":705}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":705,\"outFeatures\":75}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":75,\"outFeatures\":69}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 558-dim input: encode down to a 174-dim bottleneck and decode back to 558. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1821\nComponents:\n - input (input) params={\"shape\":[1,558]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,558]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":558,\"outFeatures\":293}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":293,\"outFeatures\":174}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":174,\"outFeatures\":293}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":293,\"outFeatures\":558}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x42x42 image with 86 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1822\nComponents:\n - input (input) params={\"shape\":[1,3,42,42]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,42,42]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":23,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":23,\"outChannels\":42,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":42,\"outChannels\":41,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":41,\"outChannels\":60,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":60,\"outFeatures\":86}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 494-token sequences with 77 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1823\nComponents:\n - input (input) params={\"shape\":[1,494]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,494]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":36164,\"embeddingDim\":20}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":20,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":20,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":20,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":20,\"outFeatures\":77}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 86-token sequences with 50 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1824\nComponents:\n - input (input) params={\"shape\":[1,86]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,86]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":30616,\"embeddingDim\":160}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":160,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[160]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":160,\"outFeatures\":50}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 3589-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1826\nComponents:\n - input (input) params={\"shape\":[1,170]}\n - fc1 (linear) params={\"inFeatures\":170,\"outFeatures\":3589}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3589,\"outFeatures\":3589}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3589,\"outFeatures\":3589}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":3589,\"outFeatures\":15}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":170,\"outFeatures\":316}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":316,\"outFeatures\":316}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":316,\"outFeatures\":316}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":316,\"outFeatures\":15}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 90-feature, 33-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1827\nComponents:\n - input (input) params={\"shape\":[1,90]}\n - fc1 (linear) params={\"inFeatures\":90,\"outFeatures\":39}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":39,\"outFeatures\":150}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":150,\"outFeatures\":34}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":34,\"outFeatures\":432}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":432,\"outFeatures\":134}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":134,\"outFeatures\":33}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":39}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":150}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":34}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":432}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":134}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 219-feature user input and a 68-feature item input, each through its own 2-layer MLP tower ending at width 351, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1828\nComponents:\n - user_input (input) params={\"shape\":[1,219]}\n - item_input (input) params={\"shape\":[1,68]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,219]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,68]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":219,\"outFeatures\":351}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":351,\"outFeatures\":351}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":68,\"outFeatures\":351}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":351,\"outFeatures\":351}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":702,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (32-feature input, 39 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1829\nComponents:\n - input (input) params={\"shape\":[1,32]}\n - fc1 (linear) params={\"inFeatures\":32,\"outFeatures\":16}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":16,\"outFeatures\":16}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":16,\"outFeatures\":39}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":32,\"outFeatures\":1118}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1118,\"outFeatures\":1118}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1118,\"outFeatures\":39}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 129-feature input with 193 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1830\nComponents:\n - input (input) params={\"shape\":[1,129]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,129]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":129,\"outFeatures\":284}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":284,\"outFeatures\":384}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":384,\"outFeatures\":75}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":75,\"outFeatures\":637}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":637,\"outFeatures\":234}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":234,\"outFeatures\":301}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":301,\"outFeatures\":193}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 320-dim input: encode down to a 96-dim bottleneck and decode back to 320. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1831\nComponents:\n - input (input) params={\"shape\":[1,320]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,320]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":320,\"outFeatures\":956}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":956,\"outFeatures\":96}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":96,\"outFeatures\":956}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":956,\"outFeatures\":320}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x50x50 image with 51 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1832\nComponents:\n - input (input) params={\"shape\":[1,3,50,50]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,50,50]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":30,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":30,\"outChannels\":13,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":13,\"outChannels\":48,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":48,\"outFeatures\":51}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 245-token sequences with 57 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1833\nComponents:\n - input (input) params={\"shape\":[1,245]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,245]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":11819,\"embeddingDim\":96}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":96,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":96,\"outFeatures\":57}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 107-token sequences with 58 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1834\nComponents:\n - input (input) params={\"shape\":[1,107]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,107]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":25245,\"embeddingDim\":384}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":384,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[384]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":384,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[384]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":384,\"outFeatures\":58}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 3575-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1836\nComponents:\n - input (input) params={\"shape\":[1,107]}\n - fc1 (linear) params={\"inFeatures\":107,\"outFeatures\":3575}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3575,\"outFeatures\":3575}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":3575,\"outFeatures\":32}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":107,\"outFeatures\":99}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":99,\"outFeatures\":99}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":99,\"outFeatures\":32}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 167-feature, 37-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1837\nComponents:\n - input (input) params={\"shape\":[1,167]}\n - fc1 (linear) params={\"inFeatures\":167,\"outFeatures\":464}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":464,\"outFeatures\":220}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":220,\"outFeatures\":160}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":160,\"outFeatures\":37}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":464}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":220}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":160}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 131-feature user input and a 203-feature item input, each through its own 2-layer MLP tower ending at width 374, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1838\nComponents:\n - user_input (input) params={\"shape\":[1,131]}\n - item_input (input) params={\"shape\":[1,203]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,131]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,203]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":131,\"outFeatures\":374}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":374,\"outFeatures\":374}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":203,\"outFeatures\":374}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":374,\"outFeatures\":374}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":748,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (58-feature input, 50 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1839\nComponents:\n - input (input) params={\"shape\":[1,58]}\n - fc1 (linear) params={\"inFeatures\":58,\"outFeatures\":15}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":15,\"outFeatures\":15}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":15,\"outFeatures\":50}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":58,\"outFeatures\":648}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":648,\"outFeatures\":648}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":648,\"outFeatures\":50}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 34-feature input with 88 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1840\nComponents:\n - input (input) params={\"shape\":[1,34]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,34]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":34,\"outFeatures\":475}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":475,\"outFeatures\":309}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":309,\"outFeatures\":357}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":357,\"outFeatures\":215}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":215,\"outFeatures\":88}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 214-dim input: encode down to a 187-dim bottleneck and decode back to 214. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1841\nComponents:\n - input (input) params={\"shape\":[1,214]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,214]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":214,\"outFeatures\":204}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":204,\"outFeatures\":187}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":187,\"outFeatures\":204}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":204,\"outFeatures\":214}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x48x48 image with 43 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1842\nComponents:\n - input (input) params={\"shape\":[1,3,48,48]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,48,48]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":18,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":18,\"outChannels\":62,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":62,\"outChannels\":44,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":44,\"outFeatures\":43}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 417-token sequences with 26 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1843\nComponents:\n - input (input) params={\"shape\":[1,417]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,417]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":12488,\"embeddingDim\":216}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":216,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":216,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":216,\"outFeatures\":26}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 369-token sequences with 57 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1844\nComponents:\n - input (input) params={\"shape\":[1,369]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,369]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":40586,\"embeddingDim\":120}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":120,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[120]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":120,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[120]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":120,\"outFeatures\":57}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3214-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1846\nComponents:\n - input (input) params={\"shape\":[1,134]}\n - fc1 (linear) params={\"inFeatures\":134,\"outFeatures\":3214}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3214,\"outFeatures\":3214}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3214,\"outFeatures\":3214}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3214,\"outFeatures\":3214}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3214,\"outFeatures\":36}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":134,\"outFeatures\":187}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":187,\"outFeatures\":187}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":187,\"outFeatures\":187}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":187,\"outFeatures\":187}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":187,\"outFeatures\":36}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 118-feature, 86-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1847\nComponents:\n - input (input) params={\"shape\":[1,118]}\n - fc1 (linear) params={\"inFeatures\":118,\"outFeatures\":344}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":344,\"outFeatures\":155}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":155,\"outFeatures\":192}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":192,\"outFeatures\":316}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":316,\"outFeatures\":413}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":413,\"outFeatures\":86}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":344}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":155}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":192}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":316}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":413}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 29-feature user input and a 230-feature item input, each through its own 2-layer MLP tower ending at width 358, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1848\nComponents:\n - user_input (input) params={\"shape\":[1,29]}\n - item_input (input) params={\"shape\":[1,230]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,29]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,230]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":29,\"outFeatures\":358}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":358,\"outFeatures\":358}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":230,\"outFeatures\":358}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":358,\"outFeatures\":358}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":716,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (65-feature input, 27 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1849\nComponents:\n - input (input) params={\"shape\":[1,65]}\n - fc1 (linear) params={\"inFeatures\":65,\"outFeatures\":13}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":13,\"outFeatures\":13}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":13,\"outFeatures\":27}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":65,\"outFeatures\":1173}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1173,\"outFeatures\":1173}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1173,\"outFeatures\":27}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 108-feature input with 148 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1850\nComponents:\n - input (input) params={\"shape\":[1,108]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,108]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":108,\"outFeatures\":911}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":911,\"outFeatures\":126}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":126,\"outFeatures\":827}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":827,\"outFeatures\":148}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 322-dim input: encode down to a 130-dim bottleneck and decode back to 322. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1851\nComponents:\n - input (input) params={\"shape\":[1,322]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,322]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":322,\"outFeatures\":67}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":67,\"outFeatures\":130}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":130,\"outFeatures\":67}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":67,\"outFeatures\":322}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x45x45 image with 96 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1852\nComponents:\n - input (input) params={\"shape\":[1,3,45,45]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,45,45]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":46,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":46,\"outChannels\":61,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":61,\"outFeatures\":96}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 278-token sequences with 87 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1853\nComponents:\n - input (input) params={\"shape\":[1,278]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,278]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":43284,\"embeddingDim\":376}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":376,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":376,\"outFeatures\":87}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 96-token sequences with 80 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1854\nComponents:\n - input (input) params={\"shape\":[1,96]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,96]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":19496,\"embeddingDim\":128}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":128,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[128]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":128,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[128]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":128,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[128]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":128,\"outFeatures\":80}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 2137-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1856\nComponents:\n - input (input) params={\"shape\":[1,64]}\n - fc1 (linear) params={\"inFeatures\":64,\"outFeatures\":2137}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2137,\"outFeatures\":2137}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2137,\"outFeatures\":2137}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":2137,\"outFeatures\":2137}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":2137,\"outFeatures\":44}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":64,\"outFeatures\":164}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":164,\"outFeatures\":164}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":164,\"outFeatures\":164}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":164,\"outFeatures\":164}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":164,\"outFeatures\":44}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 217-feature, 4-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1857\nComponents:\n - input (input) params={\"shape\":[1,217]}\n - fc1 (linear) params={\"inFeatures\":217,\"outFeatures\":39}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":39,\"outFeatures\":41}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":41,\"outFeatures\":111}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":111,\"outFeatures\":4}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":39}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":41}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":111}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 25-feature user input and a 171-feature item input, each through its own 2-layer MLP tower ending at width 205, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1858\nComponents:\n - user_input (input) params={\"shape\":[1,25]}\n - item_input (input) params={\"shape\":[1,171]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,25]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,171]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":25,\"outFeatures\":205}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":205,\"outFeatures\":205}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":171,\"outFeatures\":205}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":205,\"outFeatures\":205}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":410,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (25-feature input, 44 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1859\nComponents:\n - input (input) params={\"shape\":[1,25]}\n - fc1 (linear) params={\"inFeatures\":25,\"outFeatures\":6}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":6,\"outFeatures\":6}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":6,\"outFeatures\":44}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":25,\"outFeatures\":1015}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1015,\"outFeatures\":1015}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1015,\"outFeatures\":44}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 287-feature input with 136 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1860\nComponents:\n - input (input) params={\"shape\":[1,287]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,287]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":287,\"outFeatures\":247}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":247,\"outFeatures\":579}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":579,\"outFeatures\":495}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":495,\"outFeatures\":326}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":326,\"outFeatures\":136}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 998-dim input: encode down to a 36-dim bottleneck and decode back to 998. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1861\nComponents:\n - input (input) params={\"shape\":[1,998]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,998]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":998,\"outFeatures\":953}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":953,\"outFeatures\":36}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":36,\"outFeatures\":953}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":953,\"outFeatures\":998}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x53x53 image with 84 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1862\nComponents:\n - input (input) params={\"shape\":[1,3,53,53]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,53,53]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":10,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":10,\"outChannels\":31,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":31,\"outChannels\":41,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":41,\"outChannels\":58,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":58,\"outFeatures\":84}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 42-token sequences with 4 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1863\nComponents:\n - input (input) params={\"shape\":[1,42]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,42]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":46310,\"embeddingDim\":136}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":136,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":136,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":136,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":136,\"outFeatures\":4}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 451-token sequences with 55 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1864\nComponents:\n - input (input) params={\"shape\":[1,451]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,451]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":25173,\"embeddingDim\":84}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":84,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[84]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":84,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[84]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":84,\"outFeatures\":55}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 3575-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1866\nComponents:\n - input (input) params={\"shape\":[1,211]}\n - fc1 (linear) params={\"inFeatures\":211,\"outFeatures\":3575}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3575,\"outFeatures\":3575}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":3575,\"outFeatures\":48}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":211,\"outFeatures\":188}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":188,\"outFeatures\":188}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":188,\"outFeatures\":48}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 38-feature, 73-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1867\nComponents:\n - input (input) params={\"shape\":[1,38]}\n - fc1 (linear) params={\"inFeatures\":38,\"outFeatures\":389}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":389,\"outFeatures\":53}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":53,\"outFeatures\":73}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":389}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":53}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 56-feature user input and a 253-feature item input, each through its own 2-layer MLP tower ending at width 384, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1868\nComponents:\n - user_input (input) params={\"shape\":[1,56]}\n - item_input (input) params={\"shape\":[1,253]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,56]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,253]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":56,\"outFeatures\":384}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":384,\"outFeatures\":384}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":253,\"outFeatures\":384}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":384,\"outFeatures\":384}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":768,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (55-feature input, 28 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1869\nComponents:\n - input (input) params={\"shape\":[1,55]}\n - fc1 (linear) params={\"inFeatures\":55,\"outFeatures\":7}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":7,\"outFeatures\":7}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":7,\"outFeatures\":28}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":55,\"outFeatures\":957}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":957,\"outFeatures\":957}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":957,\"outFeatures\":28}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 80-feature input with 169 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1870\nComponents:\n - input (input) params={\"shape\":[1,80]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,80]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":80,\"outFeatures\":467}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":467,\"outFeatures\":591}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":591,\"outFeatures\":114}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":114,\"outFeatures\":408}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":408,\"outFeatures\":496}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":496,\"outFeatures\":678}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":678,\"outFeatures\":169}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1471-dim input: encode down to a 105-dim bottleneck and decode back to 1471. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1871\nComponents:\n - input (input) params={\"shape\":[1,1471]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1471]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1471,\"outFeatures\":878}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":878,\"outFeatures\":105}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":105,\"outFeatures\":878}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":878,\"outFeatures\":1471}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x62x62 image with 53 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1872\nComponents:\n - input (input) params={\"shape\":[1,3,62,62]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,62,62]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":53,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":53,\"outChannels\":36,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":36,\"outChannels\":38,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":38,\"outFeatures\":53}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 70-token sequences with 76 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1873\nComponents:\n - input (input) params={\"shape\":[1,70]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,70]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":40244,\"embeddingDim\":160}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":160,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":160,\"outFeatures\":76}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 365-token sequences with 62 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1874\nComponents:\n - input (input) params={\"shape\":[1,365]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,365]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":12847,\"embeddingDim\":624}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":624,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[624]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":624,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[624]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":624,\"outFeatures\":62}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (330) is not divisible by numHeads (7). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-1875\nComponents:\n - input (input) params={\"shape\":[1,427]}\n - embed (embedding) params={\"numEmbeddings\":32799,\"embeddingDim\":330}\n - attn (multiHeadAttention) params={\"embedDim\":330,\"numHeads\":7}\n - head (linear) params={\"inFeatures\":330,\"outFeatures\":40}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 1829-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1876\nComponents:\n - input (input) params={\"shape\":[1,76]}\n - fc1 (linear) params={\"inFeatures\":76,\"outFeatures\":1829}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":1829,\"outFeatures\":1829}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":1829,\"outFeatures\":1829}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":1829,\"outFeatures\":1829}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":1829,\"outFeatures\":14}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":76,\"outFeatures\":189}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":189,\"outFeatures\":189}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":189,\"outFeatures\":189}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":189,\"outFeatures\":189}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":189,\"outFeatures\":14}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 157-feature, 14-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1877\nComponents:\n - input (input) params={\"shape\":[1,157]}\n - fc1 (linear) params={\"inFeatures\":157,\"outFeatures\":93}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":93,\"outFeatures\":398}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":398,\"outFeatures\":389}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":389,\"outFeatures\":14}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":93}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":398}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":389}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 101-feature user input and a 245-feature item input, each through its own 2-layer MLP tower ending at width 38, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1878\nComponents:\n - user_input (input) params={\"shape\":[1,101]}\n - item_input (input) params={\"shape\":[1,245]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,101]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,245]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":101,\"outFeatures\":38}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":38,\"outFeatures\":38}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":245,\"outFeatures\":38}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":38,\"outFeatures\":38}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":76,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (54-feature input, 20 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1879\nComponents:\n - input (input) params={\"shape\":[1,54]}\n - fc1 (linear) params={\"inFeatures\":54,\"outFeatures\":6}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":6,\"outFeatures\":6}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":6,\"outFeatures\":20}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":54,\"outFeatures\":1205}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1205,\"outFeatures\":1205}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1205,\"outFeatures\":20}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 208-feature input with 72 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1880\nComponents:\n - input (input) params={\"shape\":[1,208]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,208]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":208,\"outFeatures\":560}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":560,\"outFeatures\":947}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":947,\"outFeatures\":53}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":53,\"outFeatures\":992}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":992,\"outFeatures\":394}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":394,\"outFeatures\":72}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1724-dim input: encode down to a 173-dim bottleneck and decode back to 1724. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1881\nComponents:\n - input (input) params={\"shape\":[1,1724]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1724]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1724,\"outFeatures\":770}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":770,\"outFeatures\":173}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":173,\"outFeatures\":770}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":770,\"outFeatures\":1724}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x59x59 image with 49 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1882\nComponents:\n - input (input) params={\"shape\":[1,3,59,59]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,59,59]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":33,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":33,\"outChannels\":22,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":22,\"outFeatures\":49}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 353-token sequences with 89 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1883\nComponents:\n - input (input) params={\"shape\":[1,353]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,353]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":47884,\"embeddingDim\":256}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":256,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":256,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":256,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":256,\"outFeatures\":89}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 244-token sequences with 38 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1884\nComponents:\n - input (input) params={\"shape\":[1,244]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,244]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":23476,\"embeddingDim\":100}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":100,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[100]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":100,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[100]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":100,\"outFeatures\":38}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (358) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-1885\nComponents:\n - input (input) params={\"shape\":[1,201]}\n - embed (embedding) params={\"numEmbeddings\":29999,\"embeddingDim\":358}\n - attn (multiHeadAttention) params={\"embedDim\":358,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":358,\"outFeatures\":88}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3624-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1886\nComponents:\n - input (input) params={\"shape\":[1,119]}\n - fc1 (linear) params={\"inFeatures\":119,\"outFeatures\":3624}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3624,\"outFeatures\":3624}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3624,\"outFeatures\":3624}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3624,\"outFeatures\":3624}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3624,\"outFeatures\":46}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":119,\"outFeatures\":297}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":297,\"outFeatures\":297}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":297,\"outFeatures\":297}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":297,\"outFeatures\":297}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":297,\"outFeatures\":46}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 111-feature, 28-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1887\nComponents:\n - input (input) params={\"shape\":[1,111]}\n - fc1 (linear) params={\"inFeatures\":111,\"outFeatures\":483}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":483,\"outFeatures\":192}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":192,\"outFeatures\":409}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":409,\"outFeatures\":455}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":455,\"outFeatures\":57}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":57,\"outFeatures\":28}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":483}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":192}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":409}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":455}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":57}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 94-feature user input and a 17-feature item input, each through its own 2-layer MLP tower ending at width 407, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1888\nComponents:\n - user_input (input) params={\"shape\":[1,94]}\n - item_input (input) params={\"shape\":[1,17]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,94]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,17]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":94,\"outFeatures\":407}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":407,\"outFeatures\":407}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":17,\"outFeatures\":407}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":407,\"outFeatures\":407}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":814,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (98-feature input, 13 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1889\nComponents:\n - input (input) params={\"shape\":[1,98]}\n - fc1 (linear) params={\"inFeatures\":98,\"outFeatures\":10}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":10,\"outFeatures\":10}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":10,\"outFeatures\":13}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":98,\"outFeatures\":1395}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1395,\"outFeatures\":1395}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1395,\"outFeatures\":13}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 124-feature input with 114 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1890\nComponents:\n - input (input) params={\"shape\":[1,124]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,124]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":124,\"outFeatures\":630}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":630,\"outFeatures\":581}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":581,\"outFeatures\":702}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":702,\"outFeatures\":218}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":218,\"outFeatures\":114}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1220-dim input: encode down to a 134-dim bottleneck and decode back to 1220. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1891\nComponents:\n - input (input) params={\"shape\":[1,1220]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1220]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1220,\"outFeatures\":227}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":227,\"outFeatures\":134}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":134,\"outFeatures\":227}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":227,\"outFeatures\":1220}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x36x36 image with 62 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1892\nComponents:\n - input (input) params={\"shape\":[1,3,36,36]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,36,36]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":24,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":24,\"outChannels\":45,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":45,\"outFeatures\":62}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 336-token sequences with 27 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1893\nComponents:\n - input (input) params={\"shape\":[1,336]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,336]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":21251,\"embeddingDim\":360}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":360,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":360,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":360,\"outFeatures\":27}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 124-token sequences with 39 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1894\nComponents:\n - input (input) params={\"shape\":[1,124]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,124]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":38012,\"embeddingDim\":224}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":224,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[224]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":224,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[224]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":224,\"outFeatures\":39}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3610-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1896\nComponents:\n - input (input) params={\"shape\":[1,180]}\n - fc1 (linear) params={\"inFeatures\":180,\"outFeatures\":3610}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3610,\"outFeatures\":3610}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3610,\"outFeatures\":3610}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3610,\"outFeatures\":3610}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3610,\"outFeatures\":21}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":180,\"outFeatures\":131}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":131,\"outFeatures\":131}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":131,\"outFeatures\":131}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":131,\"outFeatures\":131}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":131,\"outFeatures\":21}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 92-feature, 71-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1897\nComponents:\n - input (input) params={\"shape\":[1,92]}\n - fc1 (linear) params={\"inFeatures\":92,\"outFeatures\":349}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":349,\"outFeatures\":282}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":282,\"outFeatures\":261}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":261,\"outFeatures\":71}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":349}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":282}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":261}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 30-feature user input and a 22-feature item input, each through its own 2-layer MLP tower ending at width 233, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1898\nComponents:\n - user_input (input) params={\"shape\":[1,30]}\n - item_input (input) params={\"shape\":[1,22]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,30]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,22]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":30,\"outFeatures\":233}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":233,\"outFeatures\":233}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":22,\"outFeatures\":233}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":233,\"outFeatures\":233}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":466,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (114-feature input, 21 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1899\nComponents:\n - input (input) params={\"shape\":[1,114]}\n - fc1 (linear) params={\"inFeatures\":114,\"outFeatures\":8}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":8,\"outFeatures\":8}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":8,\"outFeatures\":21}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":114,\"outFeatures\":665}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":665,\"outFeatures\":665}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":665,\"outFeatures\":21}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 204-feature input with 67 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1900\nComponents:\n - input (input) params={\"shape\":[1,204]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,204]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":204,\"outFeatures\":120}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":120,\"outFeatures\":585}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":585,\"outFeatures\":67}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1069-dim input: encode down to a 253-dim bottleneck and decode back to 1069. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1901\nComponents:\n - input (input) params={\"shape\":[1,1069]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1069]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1069,\"outFeatures\":191}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":191,\"outFeatures\":253}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":253,\"outFeatures\":191}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":191,\"outFeatures\":1069}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x58x58 image with 53 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1902\nComponents:\n - input (input) params={\"shape\":[1,3,58,58]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,58,58]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":56,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":56,\"outChannels\":28,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":28,\"outChannels\":28,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":28,\"outFeatures\":53}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 331-token sequences with 34 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1903\nComponents:\n - input (input) params={\"shape\":[1,331]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,331]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":45503,\"embeddingDim\":304}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":304,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":304,\"outFeatures\":34}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 424-token sequences with 12 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1904\nComponents:\n - input (input) params={\"shape\":[1,424]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,424]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":33557,\"embeddingDim\":304}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":304,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[304]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":304,\"outFeatures\":12}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 2309-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1906\nComponents:\n - input (input) params={\"shape\":[1,60]}\n - fc1 (linear) params={\"inFeatures\":60,\"outFeatures\":2309}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2309,\"outFeatures\":2309}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":2309,\"outFeatures\":33}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":60,\"outFeatures\":266}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":266,\"outFeatures\":266}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":266,\"outFeatures\":33}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 95-feature, 19-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1907\nComponents:\n - input (input) params={\"shape\":[1,95]}\n - fc1 (linear) params={\"inFeatures\":95,\"outFeatures\":265}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":265,\"outFeatures\":136}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":136,\"outFeatures\":41}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":41,\"outFeatures\":433}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":433,\"outFeatures\":349}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":349,\"outFeatures\":19}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":265}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":136}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":41}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":433}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":349}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 53-feature user input and a 51-feature item input, each through its own 2-layer MLP tower ending at width 72, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1908\nComponents:\n - user_input (input) params={\"shape\":[1,53]}\n - item_input (input) params={\"shape\":[1,51]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,53]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,51]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":53,\"outFeatures\":72}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":72,\"outFeatures\":72}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":51,\"outFeatures\":72}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":72,\"outFeatures\":72}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":144,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (113-feature input, 6 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1909\nComponents:\n - input (input) params={\"shape\":[1,113]}\n - fc1 (linear) params={\"inFeatures\":113,\"outFeatures\":22}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":22,\"outFeatures\":22}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":22,\"outFeatures\":6}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":113,\"outFeatures\":1261}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1261,\"outFeatures\":1261}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1261,\"outFeatures\":6}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 22-feature input with 69 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1910\nComponents:\n - input (input) params={\"shape\":[1,22]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,22]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":22,\"outFeatures\":400}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":400,\"outFeatures\":993}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":993,\"outFeatures\":105}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":105,\"outFeatures\":69}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1207-dim input: encode down to a 156-dim bottleneck and decode back to 1207. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1911\nComponents:\n - input (input) params={\"shape\":[1,1207]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1207]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1207,\"outFeatures\":794}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":794,\"outFeatures\":156}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":156,\"outFeatures\":794}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":794,\"outFeatures\":1207}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x58x58 image with 7 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1912\nComponents:\n - input (input) params={\"shape\":[1,3,58,58]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,58,58]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":38,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":38,\"outChannels\":48,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":48,\"outChannels\":27,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":27,\"outChannels\":31,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":31,\"outFeatures\":7}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 452-token sequences with 81 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1913\nComponents:\n - input (input) params={\"shape\":[1,452]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,452]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":30597,\"embeddingDim\":160}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":160,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":160,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":160,\"outFeatures\":81}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 323-token sequences with 12 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1914\nComponents:\n - input (input) params={\"shape\":[1,323]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,323]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":13053,\"embeddingDim\":384}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":384,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[384]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":384,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[384]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":384,\"outFeatures\":12}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 4090-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1916\nComponents:\n - input (input) params={\"shape\":[1,87]}\n - fc1 (linear) params={\"inFeatures\":87,\"outFeatures\":4090}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":4090,\"outFeatures\":4090}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":4090,\"outFeatures\":29}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":87,\"outFeatures\":168}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":168,\"outFeatures\":168}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":168,\"outFeatures\":29}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 147-feature, 53-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1917\nComponents:\n - input (input) params={\"shape\":[1,147]}\n - fc1 (linear) params={\"inFeatures\":147,\"outFeatures\":240}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":240,\"outFeatures\":497}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":497,\"outFeatures\":53}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":240}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":497}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 110-feature user input and a 142-feature item input, each through its own 2-layer MLP tower ending at width 120, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1918\nComponents:\n - user_input (input) params={\"shape\":[1,110]}\n - item_input (input) params={\"shape\":[1,142]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,110]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,142]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":110,\"outFeatures\":120}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":120,\"outFeatures\":120}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":142,\"outFeatures\":120}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":120,\"outFeatures\":120}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":240,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (79-feature input, 32 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1919\nComponents:\n - input (input) params={\"shape\":[1,79]}\n - fc1 (linear) params={\"inFeatures\":79,\"outFeatures\":8}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":8,\"outFeatures\":8}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":8,\"outFeatures\":32}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":79,\"outFeatures\":863}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":863,\"outFeatures\":863}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":863,\"outFeatures\":32}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 223-feature input with 131 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1920\nComponents:\n - input (input) params={\"shape\":[1,223]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,223]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":223,\"outFeatures\":993}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":993,\"outFeatures\":820}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":820,\"outFeatures\":26}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":26,\"outFeatures\":332}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":332,\"outFeatures\":433}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":433,\"outFeatures\":415}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":415,\"outFeatures\":131}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1404-dim input: encode down to a 176-dim bottleneck and decode back to 1404. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1921\nComponents:\n - input (input) params={\"shape\":[1,1404]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1404]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1404,\"outFeatures\":831}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":831,\"outFeatures\":176}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":176,\"outFeatures\":831}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":831,\"outFeatures\":1404}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x47x47 image with 66 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1922\nComponents:\n - input (input) params={\"shape\":[1,3,47,47]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,47,47]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":25,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":25,\"outChannels\":49,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":49,\"outChannels\":16,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":16,\"outChannels\":15,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":15,\"outFeatures\":66}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 438-token sequences with 56 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1923\nComponents:\n - input (input) params={\"shape\":[1,438]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,438]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":23701,\"embeddingDim\":384}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":384,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":384,\"outFeatures\":56}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 215-token sequences with 86 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1924\nComponents:\n - input (input) params={\"shape\":[1,215]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,215]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":45938,\"embeddingDim\":432}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":432,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[432]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":432,\"outFeatures\":86}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3491-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1926\nComponents:\n - input (input) params={\"shape\":[1,138]}\n - fc1 (linear) params={\"inFeatures\":138,\"outFeatures\":3491}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3491,\"outFeatures\":3491}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3491,\"outFeatures\":3491}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3491,\"outFeatures\":3491}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3491,\"outFeatures\":22}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":138,\"outFeatures\":256}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":256,\"outFeatures\":256}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":256,\"outFeatures\":256}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":256,\"outFeatures\":256}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":256,\"outFeatures\":22}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 67-feature, 8-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1927\nComponents:\n - input (input) params={\"shape\":[1,67]}\n - fc1 (linear) params={\"inFeatures\":67,\"outFeatures\":273}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":273,\"outFeatures\":162}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":162,\"outFeatures\":423}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":423,\"outFeatures\":473}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":473,\"outFeatures\":338}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":338,\"outFeatures\":8}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":273}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":162}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":423}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":473}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":338}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 27-feature user input and a 200-feature item input, each through its own 2-layer MLP tower ending at width 39, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1928\nComponents:\n - user_input (input) params={\"shape\":[1,27]}\n - item_input (input) params={\"shape\":[1,200]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,27]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,200]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":27,\"outFeatures\":39}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":39,\"outFeatures\":39}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":200,\"outFeatures\":39}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":39,\"outFeatures\":39}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":78,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (118-feature input, 33 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1929\nComponents:\n - input (input) params={\"shape\":[1,118]}\n - fc1 (linear) params={\"inFeatures\":118,\"outFeatures\":4}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":4,\"outFeatures\":4}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":4,\"outFeatures\":33}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":118,\"outFeatures\":1093}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1093,\"outFeatures\":1093}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1093,\"outFeatures\":33}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 63-feature input with 117 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1930\nComponents:\n - input (input) params={\"shape\":[1,63]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,63]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":63,\"outFeatures\":206}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":206,\"outFeatures\":41}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":41,\"outFeatures\":117}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1861-dim input: encode down to a 92-dim bottleneck and decode back to 1861. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1931\nComponents:\n - input (input) params={\"shape\":[1,1861]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1861]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1861,\"outFeatures\":905}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":905,\"outFeatures\":92}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":92,\"outFeatures\":905}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":905,\"outFeatures\":1861}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x58x58 image with 41 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1932\nComponents:\n - input (input) params={\"shape\":[1,3,58,58]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,58,58]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":8,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":8,\"outChannels\":28,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":28,\"outFeatures\":41}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 393-token sequences with 6 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1933\nComponents:\n - input (input) params={\"shape\":[1,393]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,393]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":37552,\"embeddingDim\":78}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":78,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":78,\"outFeatures\":6}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 147-token sequences with 60 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1934\nComponents:\n - input (input) params={\"shape\":[1,147]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,147]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":28251,\"embeddingDim\":400}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":400,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[400]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":400,\"outFeatures\":60}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 1890-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1936\nComponents:\n - input (input) params={\"shape\":[1,65]}\n - fc1 (linear) params={\"inFeatures\":65,\"outFeatures\":1890}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":1890,\"outFeatures\":1890}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":1890,\"outFeatures\":1890}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":1890,\"outFeatures\":1890}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":1890,\"outFeatures\":45}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":65,\"outFeatures\":354}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":354,\"outFeatures\":354}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":354,\"outFeatures\":354}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":354,\"outFeatures\":354}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":354,\"outFeatures\":45}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 134-feature, 22-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1937\nComponents:\n - input (input) params={\"shape\":[1,134]}\n - fc1 (linear) params={\"inFeatures\":134,\"outFeatures\":62}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":62,\"outFeatures\":509}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":509,\"outFeatures\":22}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":62}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":509}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 71-feature user input and a 53-feature item input, each through its own 2-layer MLP tower ending at width 369, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1938\nComponents:\n - user_input (input) params={\"shape\":[1,71]}\n - item_input (input) params={\"shape\":[1,53]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,71]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,53]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":71,\"outFeatures\":369}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":369,\"outFeatures\":369}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":53,\"outFeatures\":369}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":369,\"outFeatures\":369}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":738,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (57-feature input, 3 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1939\nComponents:\n - input (input) params={\"shape\":[1,57]}\n - fc1 (linear) params={\"inFeatures\":57,\"outFeatures\":7}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":7,\"outFeatures\":7}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":7,\"outFeatures\":3}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":57,\"outFeatures\":948}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":948,\"outFeatures\":948}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":948,\"outFeatures\":3}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 386-feature input with 192 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1940\nComponents:\n - input (input) params={\"shape\":[1,386]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,386]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":386,\"outFeatures\":730}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":730,\"outFeatures\":690}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":690,\"outFeatures\":903}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":903,\"outFeatures\":51}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":51,\"outFeatures\":192}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1581-dim input: encode down to a 163-dim bottleneck and decode back to 1581. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1941\nComponents:\n - input (input) params={\"shape\":[1,1581]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1581]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1581,\"outFeatures\":836}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":836,\"outFeatures\":163}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":163,\"outFeatures\":836}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":836,\"outFeatures\":1581}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x60x60 image with 52 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1942\nComponents:\n - input (input) params={\"shape\":[1,3,60,60]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,60,60]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":39,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":39,\"outChannels\":55,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":55,\"outChannels\":35,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":35,\"outChannels\":31,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":31,\"outFeatures\":52}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 357-token sequences with 4 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1943\nComponents:\n - input (input) params={\"shape\":[1,357]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,357]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":25552,\"embeddingDim\":128}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":128,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":128,\"outFeatures\":4}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 363-token sequences with 68 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1944\nComponents:\n - input (input) params={\"shape\":[1,363]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,363]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":37811,\"embeddingDim\":164}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":164,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[164]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":164,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[164]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":164,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[164]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":164,\"outFeatures\":68}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 2365-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1946\nComponents:\n - input (input) params={\"shape\":[1,43]}\n - fc1 (linear) params={\"inFeatures\":43,\"outFeatures\":2365}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2365,\"outFeatures\":2365}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2365,\"outFeatures\":2365}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":2365,\"outFeatures\":48}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":43,\"outFeatures\":220}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":220,\"outFeatures\":220}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":220,\"outFeatures\":220}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":220,\"outFeatures\":48}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 216-feature, 72-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1947\nComponents:\n - input (input) params={\"shape\":[1,216]}\n - fc1 (linear) params={\"inFeatures\":216,\"outFeatures\":415}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":415,\"outFeatures\":507}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":507,\"outFeatures\":269}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":269,\"outFeatures\":72}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":415}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":507}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":269}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 149-feature user input and a 188-feature item input, each through its own 2-layer MLP tower ending at width 47, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1948\nComponents:\n - user_input (input) params={\"shape\":[1,149]}\n - item_input (input) params={\"shape\":[1,188]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,149]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,188]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":149,\"outFeatures\":47}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":47,\"outFeatures\":47}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":188,\"outFeatures\":47}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":47,\"outFeatures\":47}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":94,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (78-feature input, 18 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1949\nComponents:\n - input (input) params={\"shape\":[1,78]}\n - fc1 (linear) params={\"inFeatures\":78,\"outFeatures\":5}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":5,\"outFeatures\":5}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":5,\"outFeatures\":18}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":78,\"outFeatures\":1068}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1068,\"outFeatures\":1068}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1068,\"outFeatures\":18}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 38-feature input with 12 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1950\nComponents:\n - input (input) params={\"shape\":[1,38]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,38]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":38,\"outFeatures\":821}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":821,\"outFeatures\":925}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":925,\"outFeatures\":1000}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":1000,\"outFeatures\":12}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 870-dim input: encode down to a 184-dim bottleneck and decode back to 870. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1951\nComponents:\n - input (input) params={\"shape\":[1,870]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,870]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":870,\"outFeatures\":630}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":630,\"outFeatures\":184}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":184,\"outFeatures\":630}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":630,\"outFeatures\":870}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x30x30 image with 16 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1952\nComponents:\n - input (input) params={\"shape\":[1,3,30,30]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,30,30]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":54,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":54,\"outChannels\":30,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":30,\"outChannels\":53,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":53,\"outChannels\":27,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":27,\"outFeatures\":16}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 152-token sequences with 74 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1953\nComponents:\n - input (input) params={\"shape\":[1,152]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,152]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":25763,\"embeddingDim\":96}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":96,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":96,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":96,\"outFeatures\":74}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 154-token sequences with 77 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1954\nComponents:\n - input (input) params={\"shape\":[1,154]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,154]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":27078,\"embeddingDim\":200}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":200,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[200]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":200,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[200]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":200,\"outFeatures\":77}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 2769-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1956\nComponents:\n - input (input) params={\"shape\":[1,93]}\n - fc1 (linear) params={\"inFeatures\":93,\"outFeatures\":2769}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2769,\"outFeatures\":2769}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2769,\"outFeatures\":2769}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":2769,\"outFeatures\":30}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":93,\"outFeatures\":289}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":289,\"outFeatures\":289}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":289,\"outFeatures\":289}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":289,\"outFeatures\":30}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 178-feature, 60-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1957\nComponents:\n - input (input) params={\"shape\":[1,178]}\n - fc1 (linear) params={\"inFeatures\":178,\"outFeatures\":211}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":211,\"outFeatures\":207}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":207,\"outFeatures\":377}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":377,\"outFeatures\":308}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":308,\"outFeatures\":60}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":211}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":207}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":377}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":308}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 62-feature user input and a 35-feature item input, each through its own 2-layer MLP tower ending at width 493, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1958\nComponents:\n - user_input (input) params={\"shape\":[1,62]}\n - item_input (input) params={\"shape\":[1,35]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,62]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,35]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":62,\"outFeatures\":493}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":493,\"outFeatures\":493}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":35,\"outFeatures\":493}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":493,\"outFeatures\":493}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":986,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (80-feature input, 15 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1959\nComponents:\n - input (input) params={\"shape\":[1,80]}\n - fc1 (linear) params={\"inFeatures\":80,\"outFeatures\":5}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":5,\"outFeatures\":5}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":5,\"outFeatures\":15}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":80,\"outFeatures\":1049}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1049,\"outFeatures\":1049}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1049,\"outFeatures\":15}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 449-feature input with 12 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1960\nComponents:\n - input (input) params={\"shape\":[1,449]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,449]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":449,\"outFeatures\":147}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":147,\"outFeatures\":769}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":769,\"outFeatures\":464}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":464,\"outFeatures\":348}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":348,\"outFeatures\":12}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1730-dim input: encode down to a 206-dim bottleneck and decode back to 1730. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1961\nComponents:\n - input (input) params={\"shape\":[1,1730]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1730]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1730,\"outFeatures\":1005}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":1005,\"outFeatures\":206}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":206,\"outFeatures\":1005}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":1005,\"outFeatures\":1730}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x24x24 image with 80 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1962\nComponents:\n - input (input) params={\"shape\":[1,3,24,24]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,24,24]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":11,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":11,\"outChannels\":22,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":22,\"outChannels\":55,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":55,\"outChannels\":22,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":22,\"outFeatures\":80}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 49-token sequences with 35 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1963\nComponents:\n - input (input) params={\"shape\":[1,49]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,49]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":44647,\"embeddingDim\":120}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":120,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":120,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":120,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":120,\"outFeatures\":35}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 157-token sequences with 86 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1964\nComponents:\n - input (input) params={\"shape\":[1,157]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,157]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":16673,\"embeddingDim\":400}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":400,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[400]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":400,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[400]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":400,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[400]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":400,\"outFeatures\":86}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 3209-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1966\nComponents:\n - input (input) params={\"shape\":[1,248]}\n - fc1 (linear) params={\"inFeatures\":248,\"outFeatures\":3209}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3209,\"outFeatures\":3209}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":3209,\"outFeatures\":12}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":248,\"outFeatures\":242}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":242,\"outFeatures\":242}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":242,\"outFeatures\":12}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 57-feature, 34-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1967\nComponents:\n - input (input) params={\"shape\":[1,57]}\n - fc1 (linear) params={\"inFeatures\":57,\"outFeatures\":181}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":181,\"outFeatures\":106}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":106,\"outFeatures\":466}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":466,\"outFeatures\":491}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":491,\"outFeatures\":34}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":181}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":106}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":466}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":491}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 200-feature user input and a 104-feature item input, each through its own 2-layer MLP tower ending at width 223, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1968\nComponents:\n - user_input (input) params={\"shape\":[1,200]}\n - item_input (input) params={\"shape\":[1,104]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,200]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,104]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":200,\"outFeatures\":223}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":223,\"outFeatures\":223}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":104,\"outFeatures\":223}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":223,\"outFeatures\":223}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":446,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (125-feature input, 24 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1969\nComponents:\n - input (input) params={\"shape\":[1,125]}\n - fc1 (linear) params={\"inFeatures\":125,\"outFeatures\":20}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":20,\"outFeatures\":20}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":20,\"outFeatures\":24}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":125,\"outFeatures\":895}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":895,\"outFeatures\":895}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":895,\"outFeatures\":24}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 480-feature input with 19 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1970\nComponents:\n - input (input) params={\"shape\":[1,480]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,480]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":480,\"outFeatures\":505}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":505,\"outFeatures\":931}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":931,\"outFeatures\":19}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 337-dim input: encode down to a 160-dim bottleneck and decode back to 337. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1971\nComponents:\n - input (input) params={\"shape\":[1,337]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,337]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":337,\"outFeatures\":879}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":879,\"outFeatures\":160}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":160,\"outFeatures\":879}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":879,\"outFeatures\":337}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x57x57 image with 59 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1972\nComponents:\n - input (input) params={\"shape\":[1,3,57,57]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,57,57]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":38,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":38,\"outChannels\":64,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":64,\"outFeatures\":59}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 374-token sequences with 95 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1973\nComponents:\n - input (input) params={\"shape\":[1,374]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,374]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":23468,\"embeddingDim\":84}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":84,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":84,\"outFeatures\":95}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 150-token sequences with 75 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1974\nComponents:\n - input (input) params={\"shape\":[1,150]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,150]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":42329,\"embeddingDim\":148}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":148,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[148]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":148,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[148]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":148,\"outFeatures\":75}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3855-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1976\nComponents:\n - input (input) params={\"shape\":[1,169]}\n - fc1 (linear) params={\"inFeatures\":169,\"outFeatures\":3855}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3855,\"outFeatures\":3855}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3855,\"outFeatures\":3855}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3855,\"outFeatures\":3855}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3855,\"outFeatures\":18}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":169,\"outFeatures\":223}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":223,\"outFeatures\":223}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":223,\"outFeatures\":223}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":223,\"outFeatures\":223}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":223,\"outFeatures\":18}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 110-feature, 61-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1977\nComponents:\n - input (input) params={\"shape\":[1,110]}\n - fc1 (linear) params={\"inFeatures\":110,\"outFeatures\":384}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":384,\"outFeatures\":203}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":203,\"outFeatures\":61}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":384}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":203}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 149-feature user input and a 138-feature item input, each through its own 2-layer MLP tower ending at width 425, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1978\nComponents:\n - user_input (input) params={\"shape\":[1,149]}\n - item_input (input) params={\"shape\":[1,138]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,149]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,138]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":149,\"outFeatures\":425}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":425,\"outFeatures\":425}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":138,\"outFeatures\":425}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":425,\"outFeatures\":425}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":850,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (42-feature input, 22 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1979\nComponents:\n - input (input) params={\"shape\":[1,42]}\n - fc1 (linear) params={\"inFeatures\":42,\"outFeatures\":4}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":4,\"outFeatures\":4}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":4,\"outFeatures\":22}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":42,\"outFeatures\":963}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":963,\"outFeatures\":963}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":963,\"outFeatures\":22}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 305-feature input with 72 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1980\nComponents:\n - input (input) params={\"shape\":[1,305]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,305]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":305,\"outFeatures\":319}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":319,\"outFeatures\":969}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":969,\"outFeatures\":328}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":328,\"outFeatures\":809}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":809,\"outFeatures\":897}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":897,\"outFeatures\":72}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1487-dim input: encode down to a 148-dim bottleneck and decode back to 1487. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1981\nComponents:\n - input (input) params={\"shape\":[1,1487]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1487]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1487,\"outFeatures\":652}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":652,\"outFeatures\":148}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":148,\"outFeatures\":652}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":652,\"outFeatures\":1487}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x45x45 image with 95 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1982\nComponents:\n - input (input) params={\"shape\":[1,3,45,45]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,45,45]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":8,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":8,\"outChannels\":43,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":43,\"outChannels\":24,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":24,\"outFeatures\":95}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 147-token sequences with 40 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1983\nComponents:\n - input (input) params={\"shape\":[1,147]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,147]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":18698,\"embeddingDim\":104}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":104,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":104,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":104,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":104,\"outFeatures\":40}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 151-token sequences with 46 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1984\nComponents:\n - input (input) params={\"shape\":[1,151]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,151]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":16055,\"embeddingDim\":104}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":104,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[104]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":104,\"outFeatures\":46}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 2039-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1986\nComponents:\n - input (input) params={\"shape\":[1,145]}\n - fc1 (linear) params={\"inFeatures\":145,\"outFeatures\":2039}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2039,\"outFeatures\":2039}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2039,\"outFeatures\":2039}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":2039,\"outFeatures\":2039}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":2039,\"outFeatures\":44}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":145,\"outFeatures\":126}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":126,\"outFeatures\":126}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":126,\"outFeatures\":126}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":126,\"outFeatures\":126}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":126,\"outFeatures\":44}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 51-feature, 42-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1987\nComponents:\n - input (input) params={\"shape\":[1,51]}\n - fc1 (linear) params={\"inFeatures\":51,\"outFeatures\":32}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":32,\"outFeatures\":460}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":460,\"outFeatures\":42}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":32}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":460}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 23-feature user input and a 246-feature item input, each through its own 2-layer MLP tower ending at width 432, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1988\nComponents:\n - user_input (input) params={\"shape\":[1,23]}\n - item_input (input) params={\"shape\":[1,246]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,23]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,246]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":23,\"outFeatures\":432}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":432,\"outFeatures\":432}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":246,\"outFeatures\":432}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":432,\"outFeatures\":432}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":864,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (104-feature input, 35 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1989\nComponents:\n - input (input) params={\"shape\":[1,104]}\n - fc1 (linear) params={\"inFeatures\":104,\"outFeatures\":19}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":19,\"outFeatures\":19}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":19,\"outFeatures\":35}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":104,\"outFeatures\":1232}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1232,\"outFeatures\":1232}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1232,\"outFeatures\":35}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 403-feature input with 11 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-1990\nComponents:\n - input (input) params={\"shape\":[1,403]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,403]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":403,\"outFeatures\":455}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":455,\"outFeatures\":622}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":622,\"outFeatures\":316}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":316,\"outFeatures\":420}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":420,\"outFeatures\":11}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1357-dim input: encode down to a 123-dim bottleneck and decode back to 1357. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-1991\nComponents:\n - input (input) params={\"shape\":[1,1357]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1357]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1357,\"outFeatures\":488}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":488,\"outFeatures\":123}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":123,\"outFeatures\":488}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":488,\"outFeatures\":1357}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x49x49 image with 42 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-1992\nComponents:\n - input (input) params={\"shape\":[1,3,49,49]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,49,49]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":27,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":27,\"outChannels\":17,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":17,\"outChannels\":12,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":12,\"outChannels\":56,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":56,\"outFeatures\":42}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 259-token sequences with 8 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-1993\nComponents:\n - input (input) params={\"shape\":[1,259]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,259]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":18166,\"embeddingDim\":44}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":44,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":44,\"outFeatures\":8}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 491-token sequences with 32 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-1994\nComponents:\n - input (input) params={\"shape\":[1,491]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,491]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":36191,\"embeddingDim\":624}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":624,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[624]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":624,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[624]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":624,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[624]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":624,\"outFeatures\":32}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (324) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-1995\nComponents:\n - input (input) params={\"shape\":[1,187]}\n - embed (embedding) params={\"numEmbeddings\":9566,\"embeddingDim\":324}\n - attn (multiHeadAttention) params={\"embedDim\":324,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":324,\"outFeatures\":73}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":4}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 2595-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-1996\nComponents:\n - input (input) params={\"shape\":[1,38]}\n - fc1 (linear) params={\"inFeatures\":38,\"outFeatures\":2595}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2595,\"outFeatures\":2595}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2595,\"outFeatures\":2595}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":2595,\"outFeatures\":22}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":38,\"outFeatures\":271}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":271,\"outFeatures\":271}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":271,\"outFeatures\":271}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":271,\"outFeatures\":22}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 201-feature, 38-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-1997\nComponents:\n - input (input) params={\"shape\":[1,201]}\n - fc1 (linear) params={\"inFeatures\":201,\"outFeatures\":329}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":329,\"outFeatures\":467}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":467,\"outFeatures\":126}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":126,\"outFeatures\":38}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":329}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":467}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":126}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 43-feature user input and a 208-feature item input, each through its own 2-layer MLP tower ending at width 47, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-1998\nComponents:\n - user_input (input) params={\"shape\":[1,43]}\n - item_input (input) params={\"shape\":[1,208]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,43]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,208]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":43,\"outFeatures\":47}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":47,\"outFeatures\":47}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":208,\"outFeatures\":47}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":47,\"outFeatures\":47}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":94,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (37-feature input, 35 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-1999\nComponents:\n - input (input) params={\"shape\":[1,37]}\n - fc1 (linear) params={\"inFeatures\":37,\"outFeatures\":24}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":24,\"outFeatures\":24}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":24,\"outFeatures\":35}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":37,\"outFeatures\":741}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":741,\"outFeatures\":741}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":741,\"outFeatures\":35}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 170-feature input with 114 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2000\nComponents:\n - input (input) params={\"shape\":[1,170]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,170]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":170,\"outFeatures\":336}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":336,\"outFeatures\":782}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":782,\"outFeatures\":196}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":196,\"outFeatures\":568}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":568,\"outFeatures\":204}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":204,\"outFeatures\":114}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 2048-dim input: encode down to a 98-dim bottleneck and decode back to 2048. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2001\nComponents:\n - input (input) params={\"shape\":[1,2048]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,2048]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":2048,\"outFeatures\":760}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":760,\"outFeatures\":98}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":98,\"outFeatures\":760}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":760,\"outFeatures\":2048}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x43x43 image with 40 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2002\nComponents:\n - input (input) params={\"shape\":[1,3,43,43]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,43,43]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":56,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":56,\"outChannels\":47,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":47,\"outChannels\":45,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":45,\"outChannels\":25,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":25,\"outFeatures\":40}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 334-token sequences with 58 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2003\nComponents:\n - input (input) params={\"shape\":[1,334]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,334]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":47241,\"embeddingDim\":28}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":28,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":28,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":28,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":28,\"outFeatures\":58}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 160-token sequences with 100 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2004\nComponents:\n - input (input) params={\"shape\":[1,160]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,160]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":45634,\"embeddingDim\":60}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":60,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[60]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":60,\"outFeatures\":100}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 2536-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2006\nComponents:\n - input (input) params={\"shape\":[1,124]}\n - fc1 (linear) params={\"inFeatures\":124,\"outFeatures\":2536}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2536,\"outFeatures\":2536}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2536,\"outFeatures\":2536}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":2536,\"outFeatures\":29}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":124,\"outFeatures\":286}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":286,\"outFeatures\":286}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":286,\"outFeatures\":286}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":286,\"outFeatures\":29}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 20-feature, 16-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2007\nComponents:\n - input (input) params={\"shape\":[1,20]}\n - fc1 (linear) params={\"inFeatures\":20,\"outFeatures\":462}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":462,\"outFeatures\":272}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":272,\"outFeatures\":433}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":433,\"outFeatures\":16}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":462}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":272}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":433}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 241-feature user input and a 253-feature item input, each through its own 2-layer MLP tower ending at width 304, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2008\nComponents:\n - user_input (input) params={\"shape\":[1,241]}\n - item_input (input) params={\"shape\":[1,253]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,241]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,253]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":241,\"outFeatures\":304}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":304,\"outFeatures\":304}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":253,\"outFeatures\":304}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":304,\"outFeatures\":304}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":608,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (115-feature input, 35 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2009\nComponents:\n - input (input) params={\"shape\":[1,115]}\n - fc1 (linear) params={\"inFeatures\":115,\"outFeatures\":16}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":16,\"outFeatures\":16}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":16,\"outFeatures\":35}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":115,\"outFeatures\":1384}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1384,\"outFeatures\":1384}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1384,\"outFeatures\":35}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 318-feature input with 147 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2010\nComponents:\n - input (input) params={\"shape\":[1,318]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,318]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":318,\"outFeatures\":91}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":91,\"outFeatures\":957}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":957,\"outFeatures\":147}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1305-dim input: encode down to a 115-dim bottleneck and decode back to 1305. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2011\nComponents:\n - input (input) params={\"shape\":[1,1305]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1305]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1305,\"outFeatures\":260}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":260,\"outFeatures\":115}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":115,\"outFeatures\":260}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":260,\"outFeatures\":1305}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x35x35 image with 67 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2012\nComponents:\n - input (input) params={\"shape\":[1,3,35,35]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,35,35]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":54,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":54,\"outChannels\":34,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":34,\"outChannels\":19,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":19,\"outChannels\":58,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":58,\"outFeatures\":67}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 278-token sequences with 80 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2013\nComponents:\n - input (input) params={\"shape\":[1,278]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,278]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":26350,\"embeddingDim\":368}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":368,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":368,\"outFeatures\":80}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 373-token sequences with 70 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2014\nComponents:\n - input (input) params={\"shape\":[1,373]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,373]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":41548,\"embeddingDim\":136}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":136,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[136]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":136,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[136]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":136,\"outFeatures\":70}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (462) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-2015\nComponents:\n - input (input) params={\"shape\":[1,48]}\n - embed (embedding) params={\"numEmbeddings\":32723,\"embeddingDim\":462}\n - attn (multiHeadAttention) params={\"embedDim\":462,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":462,\"outFeatures\":87}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 3102-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2016\nComponents:\n - input (input) params={\"shape\":[1,117]}\n - fc1 (linear) params={\"inFeatures\":117,\"outFeatures\":3102}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3102,\"outFeatures\":3102}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3102,\"outFeatures\":3102}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":3102,\"outFeatures\":34}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":117,\"outFeatures\":277}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":277,\"outFeatures\":277}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":277,\"outFeatures\":277}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":277,\"outFeatures\":34}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 168-feature, 48-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2017\nComponents:\n - input (input) params={\"shape\":[1,168]}\n - fc1 (linear) params={\"inFeatures\":168,\"outFeatures\":394}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":394,\"outFeatures\":40}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":40,\"outFeatures\":82}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":82,\"outFeatures\":299}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":299,\"outFeatures\":48}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":394}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":40}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":82}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":299}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 151-feature user input and a 197-feature item input, each through its own 2-layer MLP tower ending at width 197, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2018\nComponents:\n - user_input (input) params={\"shape\":[1,151]}\n - item_input (input) params={\"shape\":[1,197]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,151]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,197]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":151,\"outFeatures\":197}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":197,\"outFeatures\":197}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":197,\"outFeatures\":197}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":197,\"outFeatures\":197}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":394,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (118-feature input, 27 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2019\nComponents:\n - input (input) params={\"shape\":[1,118]}\n - fc1 (linear) params={\"inFeatures\":118,\"outFeatures\":20}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":20,\"outFeatures\":20}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":20,\"outFeatures\":27}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":118,\"outFeatures\":1341}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1341,\"outFeatures\":1341}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1341,\"outFeatures\":27}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 165-feature input with 119 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2020\nComponents:\n - input (input) params={\"shape\":[1,165]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,165]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":165,\"outFeatures\":981}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":981,\"outFeatures\":510}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":510,\"outFeatures\":338}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":338,\"outFeatures\":646}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":646,\"outFeatures\":432}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":432,\"outFeatures\":119}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1765-dim input: encode down to a 166-dim bottleneck and decode back to 1765. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2021\nComponents:\n - input (input) params={\"shape\":[1,1765]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1765]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1765,\"outFeatures\":146}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":146,\"outFeatures\":166}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":166,\"outFeatures\":146}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":146,\"outFeatures\":1765}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x34x34 image with 65 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2022\nComponents:\n - input (input) params={\"shape\":[1,3,34,34]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,34,34]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":42,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":42,\"outChannels\":14,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":14,\"outFeatures\":65}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 132-token sequences with 59 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2023\nComponents:\n - input (input) params={\"shape\":[1,132]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,132]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":27356,\"embeddingDim\":400}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":400,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":400,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":400,\"outFeatures\":59}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 46-token sequences with 91 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2024\nComponents:\n - input (input) params={\"shape\":[1,46]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,46]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":13996,\"embeddingDim\":336}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":336,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[336]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":336,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[336]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":336,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[336]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":336,\"outFeatures\":91}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 2844-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2026\nComponents:\n - input (input) params={\"shape\":[1,235]}\n - fc1 (linear) params={\"inFeatures\":235,\"outFeatures\":2844}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2844,\"outFeatures\":2844}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2844,\"outFeatures\":2844}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":2844,\"outFeatures\":2844}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":2844,\"outFeatures\":23}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":235,\"outFeatures\":347}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":347,\"outFeatures\":347}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":347,\"outFeatures\":347}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":347,\"outFeatures\":347}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":347,\"outFeatures\":23}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 69-feature, 29-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2027\nComponents:\n - input (input) params={\"shape\":[1,69]}\n - fc1 (linear) params={\"inFeatures\":69,\"outFeatures\":309}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":309,\"outFeatures\":302}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":302,\"outFeatures\":29}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":309}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":302}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 20-feature user input and a 203-feature item input, each through its own 2-layer MLP tower ending at width 414, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2028\nComponents:\n - user_input (input) params={\"shape\":[1,20]}\n - item_input (input) params={\"shape\":[1,203]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,20]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,203]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":20,\"outFeatures\":414}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":414,\"outFeatures\":414}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":203,\"outFeatures\":414}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":414,\"outFeatures\":414}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":828,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (90-feature input, 24 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2029\nComponents:\n - input (input) params={\"shape\":[1,90]}\n - fc1 (linear) params={\"inFeatures\":90,\"outFeatures\":18}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":18,\"outFeatures\":18}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":18,\"outFeatures\":24}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":90,\"outFeatures\":898}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":898,\"outFeatures\":898}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":898,\"outFeatures\":24}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 348-feature input with 116 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2030\nComponents:\n - input (input) params={\"shape\":[1,348]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,348]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":348,\"outFeatures\":701}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":701,\"outFeatures\":511}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":511,\"outFeatures\":116}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 815-dim input: encode down to a 225-dim bottleneck and decode back to 815. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2031\nComponents:\n - input (input) params={\"shape\":[1,815]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,815]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":815,\"outFeatures\":358}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":358,\"outFeatures\":225}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":225,\"outFeatures\":358}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":358,\"outFeatures\":815}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x45x45 image with 98 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2032\nComponents:\n - input (input) params={\"shape\":[1,3,45,45]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,45,45]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":8,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":8,\"outChannels\":15,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":15,\"outChannels\":64,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":64,\"outFeatures\":98}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 313-token sequences with 60 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2033\nComponents:\n - input (input) params={\"shape\":[1,313]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,313]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":11254,\"embeddingDim\":196}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":196,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":196,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":196,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":196,\"outFeatures\":60}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 398-token sequences with 13 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2034\nComponents:\n - input (input) params={\"shape\":[1,398]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,398]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":15845,\"embeddingDim\":112}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":112,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[112]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":112,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[112]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":112,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[112]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":112,\"outFeatures\":13}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (384) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-2035\nComponents:\n - input (input) params={\"shape\":[1,178]}\n - embed (embedding) params={\"numEmbeddings\":36189,\"embeddingDim\":384}\n - attn (multiHeadAttention) params={\"embedDim\":384,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":384,\"outFeatures\":89}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":16}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 2707-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2036\nComponents:\n - input (input) params={\"shape\":[1,145]}\n - fc1 (linear) params={\"inFeatures\":145,\"outFeatures\":2707}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2707,\"outFeatures\":2707}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2707,\"outFeatures\":2707}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":2707,\"outFeatures\":2707}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":2707,\"outFeatures\":7}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":145,\"outFeatures\":263}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":263,\"outFeatures\":263}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":263,\"outFeatures\":263}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":263,\"outFeatures\":263}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":263,\"outFeatures\":7}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 108-feature, 91-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2037\nComponents:\n - input (input) params={\"shape\":[1,108]}\n - fc1 (linear) params={\"inFeatures\":108,\"outFeatures\":95}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":95,\"outFeatures\":167}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":167,\"outFeatures\":392}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":392,\"outFeatures\":91}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":95}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":167}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":392}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 204-feature user input and a 96-feature item input, each through its own 2-layer MLP tower ending at width 32, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2038\nComponents:\n - user_input (input) params={\"shape\":[1,204]}\n - item_input (input) params={\"shape\":[1,96]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,204]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,96]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":204,\"outFeatures\":32}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":32,\"outFeatures\":32}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":96,\"outFeatures\":32}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":32,\"outFeatures\":32}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":64,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (102-feature input, 2 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2039\nComponents:\n - input (input) params={\"shape\":[1,102]}\n - fc1 (linear) params={\"inFeatures\":102,\"outFeatures\":19}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":19,\"outFeatures\":19}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":19,\"outFeatures\":2}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":102,\"outFeatures\":1395}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1395,\"outFeatures\":1395}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1395,\"outFeatures\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 24-feature input with 162 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2040\nComponents:\n - input (input) params={\"shape\":[1,24]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,24]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":24,\"outFeatures\":265}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":265,\"outFeatures\":266}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":266,\"outFeatures\":961}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":961,\"outFeatures\":582}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":582,\"outFeatures\":779}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":779,\"outFeatures\":966}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":966,\"outFeatures\":162}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 784-dim input: encode down to a 59-dim bottleneck and decode back to 784. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2041\nComponents:\n - input (input) params={\"shape\":[1,784]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,784]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":784,\"outFeatures\":712}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":712,\"outFeatures\":59}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":59,\"outFeatures\":712}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":712,\"outFeatures\":784}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x48x48 image with 4 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2042\nComponents:\n - input (input) params={\"shape\":[1,3,48,48]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,48,48]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":25,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":25,\"outChannels\":64,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":64,\"outChannels\":30,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":30,\"outFeatures\":4}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 99-token sequences with 22 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2043\nComponents:\n - input (input) params={\"shape\":[1,99]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,99]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":20337,\"embeddingDim\":416}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":416,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":416,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":416,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":416,\"outFeatures\":22}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 106-token sequences with 93 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2044\nComponents:\n - input (input) params={\"shape\":[1,106]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,106]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":44851,\"embeddingDim\":52}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":52,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[52]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":52,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[52]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":52,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[52]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":52,\"outFeatures\":93}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (98) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-2045\nComponents:\n - input (input) params={\"shape\":[1,125]}\n - embed (embedding) params={\"numEmbeddings\":45096,\"embeddingDim\":98}\n - attn (multiHeadAttention) params={\"embedDim\":98,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":98,\"outFeatures\":4}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 2279-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2046\nComponents:\n - input (input) params={\"shape\":[1,55]}\n - fc1 (linear) params={\"inFeatures\":55,\"outFeatures\":2279}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2279,\"outFeatures\":2279}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":2279,\"outFeatures\":48}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":55,\"outFeatures\":377}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":377,\"outFeatures\":377}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":377,\"outFeatures\":48}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 135-feature, 85-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2047\nComponents:\n - input (input) params={\"shape\":[1,135]}\n - fc1 (linear) params={\"inFeatures\":135,\"outFeatures\":323}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":323,\"outFeatures\":461}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":461,\"outFeatures\":310}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":310,\"outFeatures\":415}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":415,\"outFeatures\":85}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":323}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":461}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":310}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":415}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 113-feature user input and a 197-feature item input, each through its own 2-layer MLP tower ending at width 271, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2048\nComponents:\n - user_input (input) params={\"shape\":[1,113]}\n - item_input (input) params={\"shape\":[1,197]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,113]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,197]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":113,\"outFeatures\":271}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":271,\"outFeatures\":271}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":197,\"outFeatures\":271}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":271,\"outFeatures\":271}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":542,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (99-feature input, 39 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2049\nComponents:\n - input (input) params={\"shape\":[1,99]}\n - fc1 (linear) params={\"inFeatures\":99,\"outFeatures\":10}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":10,\"outFeatures\":10}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":10,\"outFeatures\":39}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":99,\"outFeatures\":885}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":885,\"outFeatures\":885}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":885,\"outFeatures\":39}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 451-feature input with 103 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2050\nComponents:\n - input (input) params={\"shape\":[1,451]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,451]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":451,\"outFeatures\":405}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":405,\"outFeatures\":605}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":605,\"outFeatures\":286}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":286,\"outFeatures\":468}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":468,\"outFeatures\":103}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 2008-dim input: encode down to a 142-dim bottleneck and decode back to 2008. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2051\nComponents:\n - input (input) params={\"shape\":[1,2008]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,2008]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":2008,\"outFeatures\":85}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":85,\"outFeatures\":142}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":142,\"outFeatures\":85}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":85,\"outFeatures\":2008}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x35x35 image with 92 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2052\nComponents:\n - input (input) params={\"shape\":[1,3,35,35]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,35,35]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":62,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":62,\"outChannels\":12,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":12,\"outChannels\":58,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":58,\"outFeatures\":92}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 391-token sequences with 47 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2053\nComponents:\n - input (input) params={\"shape\":[1,391]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,391]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":41177,\"embeddingDim\":52}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":52,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":52,\"outFeatures\":47}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 70-token sequences with 91 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2054\nComponents:\n - input (input) params={\"shape\":[1,70]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,70]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":29703,\"embeddingDim\":44}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":44,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[44]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":44,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[44]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":44,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[44]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":44,\"outFeatures\":91}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (210) is not divisible by numHeads (11). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-2055\nComponents:\n - input (input) params={\"shape\":[1,355]}\n - embed (embedding) params={\"numEmbeddings\":45728,\"embeddingDim\":210}\n - attn (multiHeadAttention) params={\"embedDim\":210,\"numHeads\":11}\n - head (linear) params={\"inFeatures\":210,\"outFeatures\":47}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 3179-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2056\nComponents:\n - input (input) params={\"shape\":[1,91]}\n - fc1 (linear) params={\"inFeatures\":91,\"outFeatures\":3179}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3179,\"outFeatures\":3179}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":3179,\"outFeatures\":35}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":91,\"outFeatures\":81}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":81,\"outFeatures\":81}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":81,\"outFeatures\":35}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 124-feature, 33-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2057\nComponents:\n - input (input) params={\"shape\":[1,124]}\n - fc1 (linear) params={\"inFeatures\":124,\"outFeatures\":454}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":454,\"outFeatures\":390}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":390,\"outFeatures\":33}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":454}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":390}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 231-feature user input and a 165-feature item input, each through its own 2-layer MLP tower ending at width 276, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2058\nComponents:\n - user_input (input) params={\"shape\":[1,231]}\n - item_input (input) params={\"shape\":[1,165]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,231]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,165]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":231,\"outFeatures\":276}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":276,\"outFeatures\":276}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":165,\"outFeatures\":276}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":276,\"outFeatures\":276}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":552,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (86-feature input, 33 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2059\nComponents:\n - input (input) params={\"shape\":[1,86]}\n - fc1 (linear) params={\"inFeatures\":86,\"outFeatures\":14}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":14,\"outFeatures\":14}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":14,\"outFeatures\":33}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":86,\"outFeatures\":1132}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1132,\"outFeatures\":1132}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1132,\"outFeatures\":33}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 38-feature input with 20 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2060\nComponents:\n - input (input) params={\"shape\":[1,38]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,38]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":38,\"outFeatures\":402}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":402,\"outFeatures\":192}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":192,\"outFeatures\":793}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":793,\"outFeatures\":867}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":867,\"outFeatures\":773}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":773,\"outFeatures\":20}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1179-dim input: encode down to a 24-dim bottleneck and decode back to 1179. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2061\nComponents:\n - input (input) params={\"shape\":[1,1179]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1179]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1179,\"outFeatures\":810}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":810,\"outFeatures\":24}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":24,\"outFeatures\":810}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":810,\"outFeatures\":1179}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x60x60 image with 62 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2062\nComponents:\n - input (input) params={\"shape\":[1,3,60,60]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,60,60]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":13,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":13,\"outChannels\":33,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":33,\"outChannels\":59,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":59,\"outChannels\":17,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":17,\"outFeatures\":62}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 258-token sequences with 96 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2063\nComponents:\n - input (input) params={\"shape\":[1,258]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,258]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":10914,\"embeddingDim\":78}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":78,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":78,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":78,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":78,\"outFeatures\":96}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 204-token sequences with 33 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2064\nComponents:\n - input (input) params={\"shape\":[1,204]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,204]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":33795,\"embeddingDim\":560}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":560,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[560]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":560,\"outFeatures\":33}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 2285-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2066\nComponents:\n - input (input) params={\"shape\":[1,72]}\n - fc1 (linear) params={\"inFeatures\":72,\"outFeatures\":2285}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2285,\"outFeatures\":2285}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":2285,\"outFeatures\":25}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":72,\"outFeatures\":142}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":142,\"outFeatures\":142}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":142,\"outFeatures\":25}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 70-feature, 49-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2067\nComponents:\n - input (input) params={\"shape\":[1,70]}\n - fc1 (linear) params={\"inFeatures\":70,\"outFeatures\":251}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":251,\"outFeatures\":444}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":444,\"outFeatures\":49}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":251}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":444}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 240-feature user input and a 23-feature item input, each through its own 2-layer MLP tower ending at width 381, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2068\nComponents:\n - user_input (input) params={\"shape\":[1,240]}\n - item_input (input) params={\"shape\":[1,23]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,240]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,23]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":240,\"outFeatures\":381}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":381,\"outFeatures\":381}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":23,\"outFeatures\":381}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":381,\"outFeatures\":381}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":762,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (51-feature input, 13 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2069\nComponents:\n - input (input) params={\"shape\":[1,51]}\n - fc1 (linear) params={\"inFeatures\":51,\"outFeatures\":4}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":4,\"outFeatures\":4}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":4,\"outFeatures\":13}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":51,\"outFeatures\":645}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":645,\"outFeatures\":645}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":645,\"outFeatures\":13}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 67-feature input with 148 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2070\nComponents:\n - input (input) params={\"shape\":[1,67]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,67]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":67,\"outFeatures\":604}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":604,\"outFeatures\":342}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":342,\"outFeatures\":148}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 253-dim input: encode down to a 161-dim bottleneck and decode back to 253. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2071\nComponents:\n - input (input) params={\"shape\":[1,253]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,253]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":253,\"outFeatures\":779}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":779,\"outFeatures\":161}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":161,\"outFeatures\":779}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":779,\"outFeatures\":253}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x46x46 image with 100 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2072\nComponents:\n - input (input) params={\"shape\":[1,3,46,46]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,46,46]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":37,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":37,\"outChannels\":60,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":60,\"outChannels\":58,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":58,\"outFeatures\":100}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 315-token sequences with 33 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2073\nComponents:\n - input (input) params={\"shape\":[1,315]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,315]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":35420,\"embeddingDim\":104}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":104,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":104,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":104,\"outFeatures\":33}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 38-token sequences with 15 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2074\nComponents:\n - input (input) params={\"shape\":[1,38]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,38]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":9783,\"embeddingDim\":224}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":224,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[224]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":224,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[224]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":224,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[224]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":224,\"outFeatures\":15}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 2707-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2076\nComponents:\n - input (input) params={\"shape\":[1,206]}\n - fc1 (linear) params={\"inFeatures\":206,\"outFeatures\":2707}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2707,\"outFeatures\":2707}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2707,\"outFeatures\":2707}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":2707,\"outFeatures\":2707}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":2707,\"outFeatures\":48}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":206,\"outFeatures\":147}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":147,\"outFeatures\":147}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":147,\"outFeatures\":147}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":147,\"outFeatures\":147}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":147,\"outFeatures\":48}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 155-feature, 22-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2077\nComponents:\n - input (input) params={\"shape\":[1,155]}\n - fc1 (linear) params={\"inFeatures\":155,\"outFeatures\":430}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":430,\"outFeatures\":104}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":104,\"outFeatures\":40}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":40,\"outFeatures\":142}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":142,\"outFeatures\":276}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":276,\"outFeatures\":22}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":430}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":104}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":40}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":142}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":276}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 153-feature user input and a 101-feature item input, each through its own 2-layer MLP tower ending at width 482, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2078\nComponents:\n - user_input (input) params={\"shape\":[1,153]}\n - item_input (input) params={\"shape\":[1,101]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,153]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,101]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":153,\"outFeatures\":482}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":482,\"outFeatures\":482}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":101,\"outFeatures\":482}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":482,\"outFeatures\":482}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":964,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (107-feature input, 24 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2079\nComponents:\n - input (input) params={\"shape\":[1,107]}\n - fc1 (linear) params={\"inFeatures\":107,\"outFeatures\":11}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":11,\"outFeatures\":11}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":11,\"outFeatures\":24}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":107,\"outFeatures\":1215}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1215,\"outFeatures\":1215}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1215,\"outFeatures\":24}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 487-feature input with 175 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2080\nComponents:\n - input (input) params={\"shape\":[1,487]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,487]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":487,\"outFeatures\":694}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":694,\"outFeatures\":454}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":454,\"outFeatures\":175}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1350-dim input: encode down to a 41-dim bottleneck and decode back to 1350. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2081\nComponents:\n - input (input) params={\"shape\":[1,1350]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1350]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1350,\"outFeatures\":459}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":459,\"outFeatures\":41}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":41,\"outFeatures\":459}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":459,\"outFeatures\":1350}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x35x35 image with 5 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2082\nComponents:\n - input (input) params={\"shape\":[1,3,35,35]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,35,35]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":19,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":19,\"outChannels\":46,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":46,\"outChannels\":54,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":54,\"outFeatures\":5}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 449-token sequences with 100 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2083\nComponents:\n - input (input) params={\"shape\":[1,449]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,449]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":46420,\"embeddingDim\":312}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":312,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":312,\"outFeatures\":100}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 270-token sequences with 10 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2084\nComponents:\n - input (input) params={\"shape\":[1,270]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,270]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":38153,\"embeddingDim\":160}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":160,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[160]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":160,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[160]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":160,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[160]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":160,\"outFeatures\":10}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (88) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-2085\nComponents:\n - input (input) params={\"shape\":[1,259]}\n - embed (embedding) params={\"numEmbeddings\":8084,\"embeddingDim\":88}\n - attn (multiHeadAttention) params={\"embedDim\":88,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":88,\"outFeatures\":83}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":8}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 1585-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2086\nComponents:\n - input (input) params={\"shape\":[1,134]}\n - fc1 (linear) params={\"inFeatures\":134,\"outFeatures\":1585}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":1585,\"outFeatures\":1585}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":1585,\"outFeatures\":1585}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":1585,\"outFeatures\":1585}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":1585,\"outFeatures\":21}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":134,\"outFeatures\":153}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":153,\"outFeatures\":153}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":153,\"outFeatures\":153}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":153,\"outFeatures\":153}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":153,\"outFeatures\":21}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 19-feature, 50-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2087\nComponents:\n - input (input) params={\"shape\":[1,19]}\n - fc1 (linear) params={\"inFeatures\":19,\"outFeatures\":195}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":195,\"outFeatures\":281}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":281,\"outFeatures\":331}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":331,\"outFeatures\":50}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":50,\"outFeatures\":50}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":195}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":281}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":331}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":50}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 16-feature user input and a 140-feature item input, each through its own 2-layer MLP tower ending at width 360, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2088\nComponents:\n - user_input (input) params={\"shape\":[1,16]}\n - item_input (input) params={\"shape\":[1,140]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,16]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,140]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":16,\"outFeatures\":360}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":360,\"outFeatures\":360}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":140,\"outFeatures\":360}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":360,\"outFeatures\":360}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":720,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (70-feature input, 25 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2089\nComponents:\n - input (input) params={\"shape\":[1,70]}\n - fc1 (linear) params={\"inFeatures\":70,\"outFeatures\":16}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":16,\"outFeatures\":16}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":16,\"outFeatures\":25}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":70,\"outFeatures\":1020}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1020,\"outFeatures\":1020}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1020,\"outFeatures\":25}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 349-feature input with 104 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2090\nComponents:\n - input (input) params={\"shape\":[1,349]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,349]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":349,\"outFeatures\":628}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":628,\"outFeatures\":626}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":626,\"outFeatures\":983}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":983,\"outFeatures\":354}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":354,\"outFeatures\":446}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":446,\"outFeatures\":104}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 307-dim input: encode down to a 170-dim bottleneck and decode back to 307. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2091\nComponents:\n - input (input) params={\"shape\":[1,307]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,307]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":307,\"outFeatures\":95}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":95,\"outFeatures\":170}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":170,\"outFeatures\":95}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":95,\"outFeatures\":307}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x48x48 image with 36 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2092\nComponents:\n - input (input) params={\"shape\":[1,3,48,48]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,48,48]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":52,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":52,\"outChannels\":15,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":15,\"outFeatures\":36}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 409-token sequences with 16 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2093\nComponents:\n - input (input) params={\"shape\":[1,409]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,409]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":9331,\"embeddingDim\":184}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":184,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":184,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":184,\"outFeatures\":16}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 398-token sequences with 71 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2094\nComponents:\n - input (input) params={\"shape\":[1,398]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,398]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":43849,\"embeddingDim\":240}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":240,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[240]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":240,\"outFeatures\":71}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (214) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-2095\nComponents:\n - input (input) params={\"shape\":[1,141]}\n - embed (embedding) params={\"numEmbeddings\":25811,\"embeddingDim\":214}\n - attn (multiHeadAttention) params={\"embedDim\":214,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":214,\"outFeatures\":72}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 1638-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2096\nComponents:\n - input (input) params={\"shape\":[1,100]}\n - fc1 (linear) params={\"inFeatures\":100,\"outFeatures\":1638}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":1638,\"outFeatures\":1638}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":1638,\"outFeatures\":1638}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":1638,\"outFeatures\":1638}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":1638,\"outFeatures\":32}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":100,\"outFeatures\":100}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":100,\"outFeatures\":100}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":100,\"outFeatures\":100}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":100,\"outFeatures\":100}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":100,\"outFeatures\":32}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 69-feature, 76-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2097\nComponents:\n - input (input) params={\"shape\":[1,69]}\n - fc1 (linear) params={\"inFeatures\":69,\"outFeatures\":97}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":97,\"outFeatures\":54}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":54,\"outFeatures\":76}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":97}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":54}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 33-feature user input and a 72-feature item input, each through its own 2-layer MLP tower ending at width 51, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2098\nComponents:\n - user_input (input) params={\"shape\":[1,33]}\n - item_input (input) params={\"shape\":[1,72]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,33]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,72]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":33,\"outFeatures\":51}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":51,\"outFeatures\":51}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":72,\"outFeatures\":51}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":51,\"outFeatures\":51}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":102,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (45-feature input, 41 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2099\nComponents:\n - input (input) params={\"shape\":[1,45]}\n - fc1 (linear) params={\"inFeatures\":45,\"outFeatures\":12}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":12,\"outFeatures\":12}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":12,\"outFeatures\":41}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":45,\"outFeatures\":900}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":900,\"outFeatures\":900}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":900,\"outFeatures\":41}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 187-feature input with 50 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2100\nComponents:\n - input (input) params={\"shape\":[1,187]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,187]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":187,\"outFeatures\":370}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":370,\"outFeatures\":473}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":473,\"outFeatures\":820}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":820,\"outFeatures\":728}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":728,\"outFeatures\":619}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":619,\"outFeatures\":50}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 350-dim input: encode down to a 50-dim bottleneck and decode back to 350. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2101\nComponents:\n - input (input) params={\"shape\":[1,350]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,350]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":350,\"outFeatures\":829}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":829,\"outFeatures\":50}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":50,\"outFeatures\":829}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":829,\"outFeatures\":350}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x52x52 image with 34 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2102\nComponents:\n - input (input) params={\"shape\":[1,3,52,52]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,52,52]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":20,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":20,\"outChannels\":9,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":9,\"outChannels\":32,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":32,\"outFeatures\":34}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 309-token sequences with 27 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2103\nComponents:\n - input (input) params={\"shape\":[1,309]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,309]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":11242,\"embeddingDim\":92}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":92,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":92,\"outFeatures\":27}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 279-token sequences with 42 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2104\nComponents:\n - input (input) params={\"shape\":[1,279]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,279]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":15039,\"embeddingDim\":104}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":104,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[104]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":104,\"outFeatures\":42}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 1620-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2106\nComponents:\n - input (input) params={\"shape\":[1,131]}\n - fc1 (linear) params={\"inFeatures\":131,\"outFeatures\":1620}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":1620,\"outFeatures\":1620}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":1620,\"outFeatures\":1620}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":1620,\"outFeatures\":1620}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":1620,\"outFeatures\":10}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":131,\"outFeatures\":243}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":243,\"outFeatures\":243}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":243,\"outFeatures\":243}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":243,\"outFeatures\":243}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":243,\"outFeatures\":10}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 122-feature, 37-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2107\nComponents:\n - input (input) params={\"shape\":[1,122]}\n - fc1 (linear) params={\"inFeatures\":122,\"outFeatures\":149}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":149,\"outFeatures\":328}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":328,\"outFeatures\":37}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":149}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":328}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 147-feature user input and a 193-feature item input, each through its own 2-layer MLP tower ending at width 109, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2108\nComponents:\n - user_input (input) params={\"shape\":[1,147]}\n - item_input (input) params={\"shape\":[1,193]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,147]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,193]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":147,\"outFeatures\":109}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":109,\"outFeatures\":109}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":193,\"outFeatures\":109}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":109,\"outFeatures\":109}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":218,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (117-feature input, 23 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2109\nComponents:\n - input (input) params={\"shape\":[1,117]}\n - fc1 (linear) params={\"inFeatures\":117,\"outFeatures\":4}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":4,\"outFeatures\":4}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":4,\"outFeatures\":23}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":117,\"outFeatures\":978}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":978,\"outFeatures\":978}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":978,\"outFeatures\":23}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 421-feature input with 56 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2110\nComponents:\n - input (input) params={\"shape\":[1,421]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,421]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":421,\"outFeatures\":506}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":506,\"outFeatures\":677}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":677,\"outFeatures\":56}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1122-dim input: encode down to a 213-dim bottleneck and decode back to 1122. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2111\nComponents:\n - input (input) params={\"shape\":[1,1122]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1122]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1122,\"outFeatures\":431}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":431,\"outFeatures\":213}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":213,\"outFeatures\":431}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":431,\"outFeatures\":1122}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x32x32 image with 77 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2112\nComponents:\n - input (input) params={\"shape\":[1,3,32,32]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,32,32]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":45,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":45,\"outChannels\":27,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":27,\"outChannels\":59,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":59,\"outFeatures\":77}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 182-token sequences with 67 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2113\nComponents:\n - input (input) params={\"shape\":[1,182]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,182]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":33278,\"embeddingDim\":192}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":192,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":192,\"outFeatures\":67}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 302-token sequences with 15 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2114\nComponents:\n - input (input) params={\"shape\":[1,302]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,302]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":30356,\"embeddingDim\":368}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":368,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[368]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":368,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[368]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":368,\"outFeatures\":15}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 1791-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2116\nComponents:\n - input (input) params={\"shape\":[1,80]}\n - fc1 (linear) params={\"inFeatures\":80,\"outFeatures\":1791}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":1791,\"outFeatures\":1791}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":1791,\"outFeatures\":1791}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":1791,\"outFeatures\":1791}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":1791,\"outFeatures\":43}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":80,\"outFeatures\":259}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":259,\"outFeatures\":259}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":259,\"outFeatures\":259}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":259,\"outFeatures\":259}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":259,\"outFeatures\":43}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 49-feature, 100-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2117\nComponents:\n - input (input) params={\"shape\":[1,49]}\n - fc1 (linear) params={\"inFeatures\":49,\"outFeatures\":426}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":426,\"outFeatures\":170}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":170,\"outFeatures\":316}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":316,\"outFeatures\":100}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":426}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":170}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":316}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 217-feature user input and a 200-feature item input, each through its own 2-layer MLP tower ending at width 239, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2118\nComponents:\n - user_input (input) params={\"shape\":[1,217]}\n - item_input (input) params={\"shape\":[1,200]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,217]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,200]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":217,\"outFeatures\":239}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":239,\"outFeatures\":239}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":200,\"outFeatures\":239}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":239,\"outFeatures\":239}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":478,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (116-feature input, 49 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2119\nComponents:\n - input (input) params={\"shape\":[1,116]}\n - fc1 (linear) params={\"inFeatures\":116,\"outFeatures\":18}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":18,\"outFeatures\":18}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":18,\"outFeatures\":49}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":116,\"outFeatures\":1267}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1267,\"outFeatures\":1267}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1267,\"outFeatures\":49}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 425-feature input with 98 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2120\nComponents:\n - input (input) params={\"shape\":[1,425]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,425]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":425,\"outFeatures\":282}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":282,\"outFeatures\":488}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":488,\"outFeatures\":503}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":503,\"outFeatures\":98}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1799-dim input: encode down to a 91-dim bottleneck and decode back to 1799. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2121\nComponents:\n - input (input) params={\"shape\":[1,1799]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1799]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1799,\"outFeatures\":202}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":202,\"outFeatures\":91}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":91,\"outFeatures\":202}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":202,\"outFeatures\":1799}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x25x25 image with 23 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2122\nComponents:\n - input (input) params={\"shape\":[1,3,25,25]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,25,25]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":47,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":47,\"outChannels\":64,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":64,\"outChannels\":28,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":28,\"outFeatures\":23}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 83-token sequences with 72 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2123\nComponents:\n - input (input) params={\"shape\":[1,83]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,83]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":48368,\"embeddingDim\":52}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":52,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":52,\"outFeatures\":72}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 56-token sequences with 59 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2124\nComponents:\n - input (input) params={\"shape\":[1,56]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,56]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":9356,\"embeddingDim\":120}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":120,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[120]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":120,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[120]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":120,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[120]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":120,\"outFeatures\":59}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 2864-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2126\nComponents:\n - input (input) params={\"shape\":[1,40]}\n - fc1 (linear) params={\"inFeatures\":40,\"outFeatures\":2864}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2864,\"outFeatures\":2864}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2864,\"outFeatures\":2864}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":2864,\"outFeatures\":27}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":40,\"outFeatures\":64}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":64,\"outFeatures\":64}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":64,\"outFeatures\":64}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":64,\"outFeatures\":27}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 217-feature, 68-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2127\nComponents:\n - input (input) params={\"shape\":[1,217]}\n - fc1 (linear) params={\"inFeatures\":217,\"outFeatures\":187}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":187,\"outFeatures\":333}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":333,\"outFeatures\":242}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":242,\"outFeatures\":95}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":95,\"outFeatures\":139}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":139,\"outFeatures\":68}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":187}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":333}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":242}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":95}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":139}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 48-feature user input and a 198-feature item input, each through its own 2-layer MLP tower ending at width 408, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2128\nComponents:\n - user_input (input) params={\"shape\":[1,48]}\n - item_input (input) params={\"shape\":[1,198]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,48]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,198]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":48,\"outFeatures\":408}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":408,\"outFeatures\":408}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":198,\"outFeatures\":408}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":408,\"outFeatures\":408}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":816,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 173-feature input with 145 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2130\nComponents:\n - input (input) params={\"shape\":[1,173]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,173]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":173,\"outFeatures\":892}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":892,\"outFeatures\":39}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":39,\"outFeatures\":641}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":641,\"outFeatures\":145}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1492-dim input: encode down to a 42-dim bottleneck and decode back to 1492. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2131\nComponents:\n - input (input) params={\"shape\":[1,1492]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1492]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1492,\"outFeatures\":261}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":261,\"outFeatures\":42}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":42,\"outFeatures\":261}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":261,\"outFeatures\":1492}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x60x60 image with 26 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2132\nComponents:\n - input (input) params={\"shape\":[1,3,60,60]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,60,60]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":21,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":21,\"outChannels\":22,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":22,\"outChannels\":58,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":58,\"outFeatures\":26}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 229-token sequences with 86 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2133\nComponents:\n - input (input) params={\"shape\":[1,229]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,229]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":47187,\"embeddingDim\":48}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":48,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":48,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":48,\"outFeatures\":86}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 217-token sequences with 36 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2134\nComponents:\n - input (input) params={\"shape\":[1,217]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,217]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":22033,\"embeddingDim\":88}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":88,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[88]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":88,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[88]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":88,\"outFeatures\":36}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 3078-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2136\nComponents:\n - input (input) params={\"shape\":[1,240]}\n - fc1 (linear) params={\"inFeatures\":240,\"outFeatures\":3078}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3078,\"outFeatures\":3078}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3078,\"outFeatures\":3078}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":3078,\"outFeatures\":10}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":240,\"outFeatures\":163}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":163,\"outFeatures\":163}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":163,\"outFeatures\":163}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":163,\"outFeatures\":10}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 172-feature, 30-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2137\nComponents:\n - input (input) params={\"shape\":[1,172]}\n - fc1 (linear) params={\"inFeatures\":172,\"outFeatures\":474}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":474,\"outFeatures\":51}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":51,\"outFeatures\":391}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":391,\"outFeatures\":337}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":337,\"outFeatures\":30}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":474}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":51}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":391}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":337}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 168-feature user input and a 39-feature item input, each through its own 2-layer MLP tower ending at width 97, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2138\nComponents:\n - user_input (input) params={\"shape\":[1,168]}\n - item_input (input) params={\"shape\":[1,39]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,168]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,39]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":168,\"outFeatures\":97}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":97,\"outFeatures\":97}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":39,\"outFeatures\":97}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":97,\"outFeatures\":97}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":194,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (52-feature input, 28 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2139\nComponents:\n - input (input) params={\"shape\":[1,52]}\n - fc1 (linear) params={\"inFeatures\":52,\"outFeatures\":8}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":8,\"outFeatures\":8}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":8,\"outFeatures\":28}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":52,\"outFeatures\":793}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":793,\"outFeatures\":793}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":793,\"outFeatures\":28}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 71-feature input with 22 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2140\nComponents:\n - input (input) params={\"shape\":[1,71]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,71]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":71,\"outFeatures\":725}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":725,\"outFeatures\":616}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":616,\"outFeatures\":981}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":981,\"outFeatures\":364}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":364,\"outFeatures\":22}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1845-dim input: encode down to a 170-dim bottleneck and decode back to 1845. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2141\nComponents:\n - input (input) params={\"shape\":[1,1845]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1845]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1845,\"outFeatures\":357}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":357,\"outFeatures\":170}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":170,\"outFeatures\":357}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":357,\"outFeatures\":1845}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x42x42 image with 66 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2142\nComponents:\n - input (input) params={\"shape\":[1,3,42,42]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,42,42]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":28,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":28,\"outChannels\":21,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":21,\"outChannels\":56,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":56,\"outChannels\":44,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":44,\"outFeatures\":66}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 180-token sequences with 39 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2143\nComponents:\n - input (input) params={\"shape\":[1,180]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,180]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":45307,\"embeddingDim\":352}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":352,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":352,\"outFeatures\":39}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 261-token sequences with 10 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2144\nComponents:\n - input (input) params={\"shape\":[1,261]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,261]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":24036,\"embeddingDim\":576}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":576,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[576]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":576,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[576]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":576,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[576]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":576,\"outFeatures\":10}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (392) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-2145\nComponents:\n - input (input) params={\"shape\":[1,251]}\n - embed (embedding) params={\"numEmbeddings\":49962,\"embeddingDim\":392}\n - attn (multiHeadAttention) params={\"embedDim\":392,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":392,\"outFeatures\":3}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":8}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 3389-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2146\nComponents:\n - input (input) params={\"shape\":[1,41]}\n - fc1 (linear) params={\"inFeatures\":41,\"outFeatures\":3389}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3389,\"outFeatures\":3389}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3389,\"outFeatures\":3389}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":3389,\"outFeatures\":3}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":41,\"outFeatures\":384}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":384,\"outFeatures\":384}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":384,\"outFeatures\":384}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":384,\"outFeatures\":3}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 227-feature, 76-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2147\nComponents:\n - input (input) params={\"shape\":[1,227]}\n - fc1 (linear) params={\"inFeatures\":227,\"outFeatures\":270}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":270,\"outFeatures\":464}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":464,\"outFeatures\":253}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":253,\"outFeatures\":76}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":270}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":464}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":253}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 39-feature user input and a 19-feature item input, each through its own 2-layer MLP tower ending at width 136, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2148\nComponents:\n - user_input (input) params={\"shape\":[1,39]}\n - item_input (input) params={\"shape\":[1,19]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,39]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,19]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":39,\"outFeatures\":136}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":136,\"outFeatures\":136}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":19,\"outFeatures\":136}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":136,\"outFeatures\":136}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":272,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (99-feature input, 25 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2149\nComponents:\n - input (input) params={\"shape\":[1,99]}\n - fc1 (linear) params={\"inFeatures\":99,\"outFeatures\":7}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":7,\"outFeatures\":7}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":7,\"outFeatures\":25}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":99,\"outFeatures\":1027}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1027,\"outFeatures\":1027}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1027,\"outFeatures\":25}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 328-feature input with 67 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2150\nComponents:\n - input (input) params={\"shape\":[1,328]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,328]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":328,\"outFeatures\":426}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":426,\"outFeatures\":45}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":45,\"outFeatures\":989}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":989,\"outFeatures\":292}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":292,\"outFeatures\":67}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 826-dim input: encode down to a 120-dim bottleneck and decode back to 826. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2151\nComponents:\n - input (input) params={\"shape\":[1,826]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,826]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":826,\"outFeatures\":263}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":263,\"outFeatures\":120}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":120,\"outFeatures\":263}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":263,\"outFeatures\":826}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x63x63 image with 34 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2152\nComponents:\n - input (input) params={\"shape\":[1,3,63,63]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,63,63]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":56,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":56,\"outChannels\":12,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":12,\"outChannels\":12,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":12,\"outChannels\":52,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":52,\"outFeatures\":34}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 38-token sequences with 21 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2153\nComponents:\n - input (input) params={\"shape\":[1,38]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,38]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":45387,\"embeddingDim\":98}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":98,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":98,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":98,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":98,\"outFeatures\":21}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 490-token sequences with 6 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2154\nComponents:\n - input (input) params={\"shape\":[1,490]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,490]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":45216,\"embeddingDim\":140}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":140,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[140]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":140,\"outFeatures\":6}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 3882-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2156\nComponents:\n - input (input) params={\"shape\":[1,33]}\n - fc1 (linear) params={\"inFeatures\":33,\"outFeatures\":3882}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3882,\"outFeatures\":3882}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":3882,\"outFeatures\":26}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":33,\"outFeatures\":67}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":67,\"outFeatures\":67}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":67,\"outFeatures\":26}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 226-feature, 67-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2157\nComponents:\n - input (input) params={\"shape\":[1,226]}\n - fc1 (linear) params={\"inFeatures\":226,\"outFeatures\":112}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":112,\"outFeatures\":350}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":350,\"outFeatures\":456}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":456,\"outFeatures\":67}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":112}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":350}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":456}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 217-feature user input and a 178-feature item input, each through its own 2-layer MLP tower ending at width 94, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2158\nComponents:\n - user_input (input) params={\"shape\":[1,217]}\n - item_input (input) params={\"shape\":[1,178]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,217]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,178]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":217,\"outFeatures\":94}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":94,\"outFeatures\":94}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":178,\"outFeatures\":94}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":94,\"outFeatures\":94}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":188,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (79-feature input, 16 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2159\nComponents:\n - input (input) params={\"shape\":[1,79]}\n - fc1 (linear) params={\"inFeatures\":79,\"outFeatures\":12}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":12,\"outFeatures\":12}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":12,\"outFeatures\":16}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":79,\"outFeatures\":1065}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1065,\"outFeatures\":1065}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1065,\"outFeatures\":16}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 308-feature input with 140 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2160\nComponents:\n - input (input) params={\"shape\":[1,308]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,308]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":308,\"outFeatures\":474}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":474,\"outFeatures\":323}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":323,\"outFeatures\":303}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":303,\"outFeatures\":686}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":686,\"outFeatures\":250}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":250,\"outFeatures\":140}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1414-dim input: encode down to a 256-dim bottleneck and decode back to 1414. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2161\nComponents:\n - input (input) params={\"shape\":[1,1414]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1414]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1414,\"outFeatures\":190}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":190,\"outFeatures\":256}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":256,\"outFeatures\":190}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":190,\"outFeatures\":1414}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x38x38 image with 100 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2162\nComponents:\n - input (input) params={\"shape\":[1,3,38,38]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,38,38]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":10,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":10,\"outChannels\":35,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":35,\"outChannels\":60,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":60,\"outChannels\":19,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":19,\"outFeatures\":100}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 282-token sequences with 38 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2163\nComponents:\n - input (input) params={\"shape\":[1,282]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,282]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":14252,\"embeddingDim\":172}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":172,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":172,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":172,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":172,\"outFeatures\":38}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 382-token sequences with 32 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2164\nComponents:\n - input (input) params={\"shape\":[1,382]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,382]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":42909,\"embeddingDim\":68}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":68,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[68]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":68,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[68]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":68,\"outFeatures\":32}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (72) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-2165\nComponents:\n - input (input) params={\"shape\":[1,252]}\n - embed (embedding) params={\"numEmbeddings\":37225,\"embeddingDim\":72}\n - attn (multiHeadAttention) params={\"embedDim\":72,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":72,\"outFeatures\":81}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":8}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 4040-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2166\nComponents:\n - input (input) params={\"shape\":[1,63]}\n - fc1 (linear) params={\"inFeatures\":63,\"outFeatures\":4040}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":4040,\"outFeatures\":4040}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":4040,\"outFeatures\":4040}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":4040,\"outFeatures\":15}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":63,\"outFeatures\":250}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":250,\"outFeatures\":250}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":250,\"outFeatures\":250}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":250,\"outFeatures\":15}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 159-feature, 17-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2167\nComponents:\n - input (input) params={\"shape\":[1,159]}\n - fc1 (linear) params={\"inFeatures\":159,\"outFeatures\":161}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":161,\"outFeatures\":447}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":447,\"outFeatures\":402}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":402,\"outFeatures\":17}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":161}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":447}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":402}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 170-feature user input and a 38-feature item input, each through its own 2-layer MLP tower ending at width 441, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2168\nComponents:\n - user_input (input) params={\"shape\":[1,170]}\n - item_input (input) params={\"shape\":[1,38]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,170]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,38]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":170,\"outFeatures\":441}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":441,\"outFeatures\":441}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":38,\"outFeatures\":441}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":441,\"outFeatures\":441}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":882,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (118-feature input, 38 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2169\nComponents:\n - input (input) params={\"shape\":[1,118]}\n - fc1 (linear) params={\"inFeatures\":118,\"outFeatures\":5}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":5,\"outFeatures\":5}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":5,\"outFeatures\":38}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":118,\"outFeatures\":1119}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1119,\"outFeatures\":1119}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1119,\"outFeatures\":38}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 487-feature input with 42 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2170\nComponents:\n - input (input) params={\"shape\":[1,487]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,487]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":487,\"outFeatures\":632}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":632,\"outFeatures\":69}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":69,\"outFeatures\":854}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":854,\"outFeatures\":918}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":918,\"outFeatures\":766}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":766,\"outFeatures\":42}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 619-dim input: encode down to a 191-dim bottleneck and decode back to 619. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2171\nComponents:\n - input (input) params={\"shape\":[1,619]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,619]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":619,\"outFeatures\":586}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":586,\"outFeatures\":191}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":191,\"outFeatures\":586}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":586,\"outFeatures\":619}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x28x28 image with 95 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2172\nComponents:\n - input (input) params={\"shape\":[1,3,28,28]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,28,28]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":33,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":33,\"outChannels\":12,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":12,\"outChannels\":33,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":33,\"outChannels\":58,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":58,\"outFeatures\":95}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 151-token sequences with 82 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2173\nComponents:\n - input (input) params={\"shape\":[1,151]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,151]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":8842,\"embeddingDim\":116}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":116,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":116,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":116,\"outFeatures\":82}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 315-token sequences with 91 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2174\nComponents:\n - input (input) params={\"shape\":[1,315]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,315]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":35654,\"embeddingDim\":84}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":84,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[84]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":84,\"outFeatures\":91}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 1989-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2176\nComponents:\n - input (input) params={\"shape\":[1,193]}\n - fc1 (linear) params={\"inFeatures\":193,\"outFeatures\":1989}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":1989,\"outFeatures\":1989}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":1989,\"outFeatures\":1989}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":1989,\"outFeatures\":1989}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":1989,\"outFeatures\":17}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":193,\"outFeatures\":129}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":129,\"outFeatures\":129}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":129,\"outFeatures\":129}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":129,\"outFeatures\":129}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":129,\"outFeatures\":17}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 146-feature, 4-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2177\nComponents:\n - input (input) params={\"shape\":[1,146]}\n - fc1 (linear) params={\"inFeatures\":146,\"outFeatures\":407}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":407,\"outFeatures\":415}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":415,\"outFeatures\":239}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":239,\"outFeatures\":4}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":407}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":415}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":239}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 209-feature user input and a 88-feature item input, each through its own 2-layer MLP tower ending at width 310, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2178\nComponents:\n - user_input (input) params={\"shape\":[1,209]}\n - item_input (input) params={\"shape\":[1,88]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,209]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,88]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":209,\"outFeatures\":310}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":310,\"outFeatures\":310}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":88,\"outFeatures\":310}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":310,\"outFeatures\":310}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":620,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (64-feature input, 35 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2179\nComponents:\n - input (input) params={\"shape\":[1,64]}\n - fc1 (linear) params={\"inFeatures\":64,\"outFeatures\":17}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":17,\"outFeatures\":17}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":17,\"outFeatures\":35}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":64,\"outFeatures\":830}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":830,\"outFeatures\":830}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":830,\"outFeatures\":35}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 164-feature input with 71 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2180\nComponents:\n - input (input) params={\"shape\":[1,164]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,164]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":164,\"outFeatures\":108}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":108,\"outFeatures\":73}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":73,\"outFeatures\":464}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":464,\"outFeatures\":233}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":233,\"outFeatures\":524}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":524,\"outFeatures\":71}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 254-dim input: encode down to a 239-dim bottleneck and decode back to 254. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2181\nComponents:\n - input (input) params={\"shape\":[1,254]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,254]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":254,\"outFeatures\":731}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":731,\"outFeatures\":239}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":239,\"outFeatures\":731}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":731,\"outFeatures\":254}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x26x26 image with 72 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2182\nComponents:\n - input (input) params={\"shape\":[1,3,26,26]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,26,26]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":13,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":13,\"outChannels\":47,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":47,\"outFeatures\":72}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 178-token sequences with 36 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2183\nComponents:\n - input (input) params={\"shape\":[1,178]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,178]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":28712,\"embeddingDim\":54}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":54,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":54,\"outFeatures\":36}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 126-token sequences with 51 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2184\nComponents:\n - input (input) params={\"shape\":[1,126]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,126]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":37599,\"embeddingDim\":104}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":104,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[104]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":104,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[104]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":104,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[104]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":104,\"outFeatures\":51}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (366) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-2185\nComponents:\n - input (input) params={\"shape\":[1,320]}\n - embed (embedding) params={\"numEmbeddings\":20637,\"embeddingDim\":366}\n - attn (multiHeadAttention) params={\"embedDim\":366,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":366,\"outFeatures\":61}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3440-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2186\nComponents:\n - input (input) params={\"shape\":[1,44]}\n - fc1 (linear) params={\"inFeatures\":44,\"outFeatures\":3440}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3440,\"outFeatures\":3440}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3440,\"outFeatures\":3440}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3440,\"outFeatures\":3440}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3440,\"outFeatures\":44}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":44,\"outFeatures\":237}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":237,\"outFeatures\":237}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":237,\"outFeatures\":237}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":237,\"outFeatures\":237}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":237,\"outFeatures\":44}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 191-feature, 70-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2187\nComponents:\n - input (input) params={\"shape\":[1,191]}\n - fc1 (linear) params={\"inFeatures\":191,\"outFeatures\":250}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":250,\"outFeatures\":416}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":416,\"outFeatures\":168}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":168,\"outFeatures\":70}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":250}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":416}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":168}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 63-feature user input and a 199-feature item input, each through its own 2-layer MLP tower ending at width 367, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2188\nComponents:\n - user_input (input) params={\"shape\":[1,63]}\n - item_input (input) params={\"shape\":[1,199]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,63]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,199]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":63,\"outFeatures\":367}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":367,\"outFeatures\":367}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":199,\"outFeatures\":367}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":367,\"outFeatures\":367}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":734,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (29-feature input, 26 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2189\nComponents:\n - input (input) params={\"shape\":[1,29]}\n - fc1 (linear) params={\"inFeatures\":29,\"outFeatures\":16}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":16,\"outFeatures\":16}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":16,\"outFeatures\":26}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":29,\"outFeatures\":1393}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1393,\"outFeatures\":1393}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1393,\"outFeatures\":26}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 472-feature input with 175 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2190\nComponents:\n - input (input) params={\"shape\":[1,472]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,472]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":472,\"outFeatures\":145}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":145,\"outFeatures\":1004}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":1004,\"outFeatures\":287}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":287,\"outFeatures\":710}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":710,\"outFeatures\":588}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":588,\"outFeatures\":175}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1540-dim input: encode down to a 50-dim bottleneck and decode back to 1540. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2191\nComponents:\n - input (input) params={\"shape\":[1,1540]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1540]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1540,\"outFeatures\":229}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":229,\"outFeatures\":50}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":50,\"outFeatures\":229}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":229,\"outFeatures\":1540}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x31x31 image with 13 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2192\nComponents:\n - input (input) params={\"shape\":[1,3,31,31]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,31,31]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":47,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":47,\"outChannels\":42,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":42,\"outChannels\":64,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":64,\"outFeatures\":13}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 267-token sequences with 98 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2193\nComponents:\n - input (input) params={\"shape\":[1,267]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,267]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":38524,\"embeddingDim\":184}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":184,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":184,\"outFeatures\":98}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 283-token sequences with 73 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2194\nComponents:\n - input (input) params={\"shape\":[1,283]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,283]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":30976,\"embeddingDim\":544}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":544,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[544]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":544,\"outFeatures\":73}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (228) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-2195\nComponents:\n - input (input) params={\"shape\":[1,496]}\n - embed (embedding) params={\"numEmbeddings\":28899,\"embeddingDim\":228}\n - attn (multiHeadAttention) params={\"embedDim\":228,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":228,\"outFeatures\":73}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":4}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 2503-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2196\nComponents:\n - input (input) params={\"shape\":[1,203]}\n - fc1 (linear) params={\"inFeatures\":203,\"outFeatures\":2503}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2503,\"outFeatures\":2503}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2503,\"outFeatures\":2503}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":2503,\"outFeatures\":13}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":203,\"outFeatures\":360}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":360,\"outFeatures\":360}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":360,\"outFeatures\":360}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":360,\"outFeatures\":13}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 98-feature, 68-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2197\nComponents:\n - input (input) params={\"shape\":[1,98]}\n - fc1 (linear) params={\"inFeatures\":98,\"outFeatures\":189}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":189,\"outFeatures\":163}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":163,\"outFeatures\":68}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":189}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":163}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 214-feature user input and a 132-feature item input, each through its own 2-layer MLP tower ending at width 117, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2198\nComponents:\n - user_input (input) params={\"shape\":[1,214]}\n - item_input (input) params={\"shape\":[1,132]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,214]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,132]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":214,\"outFeatures\":117}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":117,\"outFeatures\":117}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":132,\"outFeatures\":117}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":117,\"outFeatures\":117}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":234,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (35-feature input, 49 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2199\nComponents:\n - input (input) params={\"shape\":[1,35]}\n - fc1 (linear) params={\"inFeatures\":35,\"outFeatures\":23}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":23,\"outFeatures\":23}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":23,\"outFeatures\":49}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":35,\"outFeatures\":1268}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1268,\"outFeatures\":1268}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1268,\"outFeatures\":49}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 274-feature input with 101 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2200\nComponents:\n - input (input) params={\"shape\":[1,274]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,274]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":274,\"outFeatures\":303}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":303,\"outFeatures\":940}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":940,\"outFeatures\":408}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":408,\"outFeatures\":101}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1514-dim input: encode down to a 148-dim bottleneck and decode back to 1514. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2201\nComponents:\n - input (input) params={\"shape\":[1,1514]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1514]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1514,\"outFeatures\":341}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":341,\"outFeatures\":148}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":148,\"outFeatures\":341}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":341,\"outFeatures\":1514}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x55x55 image with 3 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2202\nComponents:\n - input (input) params={\"shape\":[1,3,55,55]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,55,55]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":15,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":15,\"outChannels\":63,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":63,\"outFeatures\":3}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 61-token sequences with 32 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2203\nComponents:\n - input (input) params={\"shape\":[1,61]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,61]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":42502,\"embeddingDim\":52}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":52,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":52,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":52,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":52,\"outFeatures\":32}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 335-token sequences with 9 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2204\nComponents:\n - input (input) params={\"shape\":[1,335]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,335]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":36252,\"embeddingDim\":376}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":376,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[376]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":376,\"outFeatures\":9}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 3943-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2206\nComponents:\n - input (input) params={\"shape\":[1,37]}\n - fc1 (linear) params={\"inFeatures\":37,\"outFeatures\":3943}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3943,\"outFeatures\":3943}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3943,\"outFeatures\":3943}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":3943,\"outFeatures\":31}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":37,\"outFeatures\":357}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":357,\"outFeatures\":357}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":357,\"outFeatures\":357}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":357,\"outFeatures\":31}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 110-feature, 53-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2207\nComponents:\n - input (input) params={\"shape\":[1,110]}\n - fc1 (linear) params={\"inFeatures\":110,\"outFeatures\":85}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":85,\"outFeatures\":277}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":277,\"outFeatures\":34}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":34,\"outFeatures\":279}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":279,\"outFeatures\":109}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":109,\"outFeatures\":53}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":85}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":277}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":34}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":279}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":109}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 201-feature user input and a 187-feature item input, each through its own 2-layer MLP tower ending at width 490, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2208\nComponents:\n - user_input (input) params={\"shape\":[1,201]}\n - item_input (input) params={\"shape\":[1,187]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,201]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,187]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":201,\"outFeatures\":490}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":490,\"outFeatures\":490}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":187,\"outFeatures\":490}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":490,\"outFeatures\":490}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":980,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (41-feature input, 3 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2209\nComponents:\n - input (input) params={\"shape\":[1,41]}\n - fc1 (linear) params={\"inFeatures\":41,\"outFeatures\":6}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":6,\"outFeatures\":6}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":6,\"outFeatures\":3}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":41,\"outFeatures\":711}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":711,\"outFeatures\":711}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":711,\"outFeatures\":3}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 422-feature input with 68 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2210\nComponents:\n - input (input) params={\"shape\":[1,422]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,422]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":422,\"outFeatures\":164}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":164,\"outFeatures\":662}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":662,\"outFeatures\":342}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":342,\"outFeatures\":1005}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":1005,\"outFeatures\":68}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1732-dim input: encode down to a 93-dim bottleneck and decode back to 1732. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2211\nComponents:\n - input (input) params={\"shape\":[1,1732]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1732]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1732,\"outFeatures\":976}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":976,\"outFeatures\":93}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":93,\"outFeatures\":976}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":976,\"outFeatures\":1732}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x51x51 image with 100 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2212\nComponents:\n - input (input) params={\"shape\":[1,3,51,51]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,51,51]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":28,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":28,\"outChannels\":47,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":47,\"outChannels\":38,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":38,\"outChannels\":18,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":18,\"outFeatures\":100}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 461-token sequences with 40 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2213\nComponents:\n - input (input) params={\"shape\":[1,461]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,461]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":47873,\"embeddingDim\":60}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":60,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":60,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":60,\"outFeatures\":40}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 85-token sequences with 57 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2214\nComponents:\n - input (input) params={\"shape\":[1,85]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,85]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":38775,\"embeddingDim\":88}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":88,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[88]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":88,\"outFeatures\":57}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 2437-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2216\nComponents:\n - input (input) params={\"shape\":[1,203]}\n - fc1 (linear) params={\"inFeatures\":203,\"outFeatures\":2437}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2437,\"outFeatures\":2437}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2437,\"outFeatures\":2437}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":2437,\"outFeatures\":2437}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":2437,\"outFeatures\":13}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":203,\"outFeatures\":256}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":256,\"outFeatures\":256}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":256,\"outFeatures\":256}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":256,\"outFeatures\":256}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":256,\"outFeatures\":13}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 16-feature, 7-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2217\nComponents:\n - input (input) params={\"shape\":[1,16]}\n - fc1 (linear) params={\"inFeatures\":16,\"outFeatures\":329}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":329,\"outFeatures\":71}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":71,\"outFeatures\":339}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":339,\"outFeatures\":52}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":52,\"outFeatures\":250}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":250,\"outFeatures\":7}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":329}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":71}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":339}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":52}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":250}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 204-feature user input and a 252-feature item input, each through its own 2-layer MLP tower ending at width 124, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2218\nComponents:\n - user_input (input) params={\"shape\":[1,204]}\n - item_input (input) params={\"shape\":[1,252]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,204]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,252]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":204,\"outFeatures\":124}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":124,\"outFeatures\":124}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":252,\"outFeatures\":124}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":124,\"outFeatures\":124}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":248,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (38-feature input, 40 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2219\nComponents:\n - input (input) params={\"shape\":[1,38]}\n - fc1 (linear) params={\"inFeatures\":38,\"outFeatures\":22}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":22,\"outFeatures\":22}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":22,\"outFeatures\":40}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":38,\"outFeatures\":729}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":729,\"outFeatures\":729}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":729,\"outFeatures\":40}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 214-feature input with 129 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2220\nComponents:\n - input (input) params={\"shape\":[1,214]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,214]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":214,\"outFeatures\":596}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":596,\"outFeatures\":974}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":974,\"outFeatures\":129}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1784-dim input: encode down to a 38-dim bottleneck and decode back to 1784. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2221\nComponents:\n - input (input) params={\"shape\":[1,1784]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1784]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1784,\"outFeatures\":420}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":420,\"outFeatures\":38}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":38,\"outFeatures\":420}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":420,\"outFeatures\":1784}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x24x24 image with 4 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2222\nComponents:\n - input (input) params={\"shape\":[1,3,24,24]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,24,24]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":55,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":55,\"outChannels\":54,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":54,\"outChannels\":9,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":9,\"outChannels\":49,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":49,\"outFeatures\":4}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 179-token sequences with 66 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2223\nComponents:\n - input (input) params={\"shape\":[1,179]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,179]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":46629,\"embeddingDim\":98}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":98,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":98,\"outFeatures\":66}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 123-token sequences with 66 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2224\nComponents:\n - input (input) params={\"shape\":[1,123]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,123]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":36357,\"embeddingDim\":168}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":168,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[168]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":168,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[168]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":168,\"outFeatures\":66}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3342-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2226\nComponents:\n - input (input) params={\"shape\":[1,145]}\n - fc1 (linear) params={\"inFeatures\":145,\"outFeatures\":3342}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3342,\"outFeatures\":3342}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3342,\"outFeatures\":3342}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3342,\"outFeatures\":3342}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3342,\"outFeatures\":16}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":145,\"outFeatures\":68}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":68,\"outFeatures\":68}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":68,\"outFeatures\":68}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":68,\"outFeatures\":68}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":68,\"outFeatures\":16}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 53-feature, 50-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2227\nComponents:\n - input (input) params={\"shape\":[1,53]}\n - fc1 (linear) params={\"inFeatures\":53,\"outFeatures\":496}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":496,\"outFeatures\":300}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":300,\"outFeatures\":50}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":496}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":300}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 81-feature user input and a 174-feature item input, each through its own 2-layer MLP tower ending at width 290, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2228\nComponents:\n - user_input (input) params={\"shape\":[1,81]}\n - item_input (input) params={\"shape\":[1,174]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,81]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,174]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":81,\"outFeatures\":290}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":290,\"outFeatures\":290}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":174,\"outFeatures\":290}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":290,\"outFeatures\":290}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":580,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (114-feature input, 24 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2229\nComponents:\n - input (input) params={\"shape\":[1,114]}\n - fc1 (linear) params={\"inFeatures\":114,\"outFeatures\":22}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":22,\"outFeatures\":22}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":22,\"outFeatures\":24}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":114,\"outFeatures\":1156}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1156,\"outFeatures\":1156}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1156,\"outFeatures\":24}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 171-feature input with 188 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2230\nComponents:\n - input (input) params={\"shape\":[1,171]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,171]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":171,\"outFeatures\":204}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":204,\"outFeatures\":791}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":791,\"outFeatures\":412}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":412,\"outFeatures\":95}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":95,\"outFeatures\":653}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":653,\"outFeatures\":662}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":662,\"outFeatures\":188}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 555-dim input: encode down to a 236-dim bottleneck and decode back to 555. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2231\nComponents:\n - input (input) params={\"shape\":[1,555]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,555]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":555,\"outFeatures\":514}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":514,\"outFeatures\":236}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":236,\"outFeatures\":514}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":514,\"outFeatures\":555}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x39x39 image with 88 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2232\nComponents:\n - input (input) params={\"shape\":[1,3,39,39]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,39,39]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":63,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":63,\"outChannels\":42,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":42,\"outFeatures\":88}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 64-token sequences with 100 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2233\nComponents:\n - input (input) params={\"shape\":[1,64]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,64]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":8676,\"embeddingDim\":136}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":136,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":136,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":136,\"outFeatures\":100}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 239-token sequences with 79 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2234\nComponents:\n - input (input) params={\"shape\":[1,239]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,239]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":23884,\"embeddingDim\":624}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":624,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[624]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":624,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[624]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":624,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[624]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":624,\"outFeatures\":79}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (146) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-2235\nComponents:\n - input (input) params={\"shape\":[1,323]}\n - embed (embedding) params={\"numEmbeddings\":31746,\"embeddingDim\":146}\n - attn (multiHeadAttention) params={\"embedDim\":146,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":146,\"outFeatures\":26}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 3330-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2236\nComponents:\n - input (input) params={\"shape\":[1,116]}\n - fc1 (linear) params={\"inFeatures\":116,\"outFeatures\":3330}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3330,\"outFeatures\":3330}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":3330,\"outFeatures\":10}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":116,\"outFeatures\":98}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":98,\"outFeatures\":98}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":98,\"outFeatures\":10}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 132-feature, 57-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2237\nComponents:\n - input (input) params={\"shape\":[1,132]}\n - fc1 (linear) params={\"inFeatures\":132,\"outFeatures\":114}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":114,\"outFeatures\":469}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":469,\"outFeatures\":509}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":509,\"outFeatures\":57}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":114}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":469}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":509}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 203-feature user input and a 197-feature item input, each through its own 2-layer MLP tower ending at width 427, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2238\nComponents:\n - user_input (input) params={\"shape\":[1,203]}\n - item_input (input) params={\"shape\":[1,197]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,203]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,197]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":203,\"outFeatures\":427}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":427,\"outFeatures\":427}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":197,\"outFeatures\":427}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":427,\"outFeatures\":427}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":854,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (79-feature input, 23 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2239\nComponents:\n - input (input) params={\"shape\":[1,79]}\n - fc1 (linear) params={\"inFeatures\":79,\"outFeatures\":20}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":20,\"outFeatures\":20}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":20,\"outFeatures\":23}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":79,\"outFeatures\":1338}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1338,\"outFeatures\":1338}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1338,\"outFeatures\":23}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 86-feature input with 145 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2240\nComponents:\n - input (input) params={\"shape\":[1,86]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,86]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":86,\"outFeatures\":682}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":682,\"outFeatures\":306}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":306,\"outFeatures\":580}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":580,\"outFeatures\":772}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":772,\"outFeatures\":501}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":501,\"outFeatures\":175}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":175,\"outFeatures\":145}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1063-dim input: encode down to a 134-dim bottleneck and decode back to 1063. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2241\nComponents:\n - input (input) params={\"shape\":[1,1063]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1063]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1063,\"outFeatures\":456}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":456,\"outFeatures\":134}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":134,\"outFeatures\":456}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":456,\"outFeatures\":1063}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x33x33 image with 86 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2242\nComponents:\n - input (input) params={\"shape\":[1,3,33,33]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,33,33]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":63,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":63,\"outChannels\":43,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":43,\"outFeatures\":86}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 272-token sequences with 69 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2243\nComponents:\n - input (input) params={\"shape\":[1,272]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,272]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":22543,\"embeddingDim\":60}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":60,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":60,\"outFeatures\":69}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 138-token sequences with 15 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2244\nComponents:\n - input (input) params={\"shape\":[1,138]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,138]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":49428,\"embeddingDim\":72}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":72,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[72]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":72,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[72]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":72,\"outFeatures\":15}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (94) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-2245\nComponents:\n - input (input) params={\"shape\":[1,328]}\n - embed (embedding) params={\"numEmbeddings\":19735,\"embeddingDim\":94}\n - attn (multiHeadAttention) params={\"embedDim\":94,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":94,\"outFeatures\":31}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 2404-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2246\nComponents:\n - input (input) params={\"shape\":[1,171]}\n - fc1 (linear) params={\"inFeatures\":171,\"outFeatures\":2404}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2404,\"outFeatures\":2404}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2404,\"outFeatures\":2404}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":2404,\"outFeatures\":49}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":171,\"outFeatures\":372}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":372,\"outFeatures\":372}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":372,\"outFeatures\":372}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":372,\"outFeatures\":49}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 56-feature, 53-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2247\nComponents:\n - input (input) params={\"shape\":[1,56]}\n - fc1 (linear) params={\"inFeatures\":56,\"outFeatures\":244}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":244,\"outFeatures\":441}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":441,\"outFeatures\":91}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":91,\"outFeatures\":439}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":439,\"outFeatures\":496}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":496,\"outFeatures\":53}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":244}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":441}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":91}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":439}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":496}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 158-feature user input and a 108-feature item input, each through its own 2-layer MLP tower ending at width 434, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2248\nComponents:\n - user_input (input) params={\"shape\":[1,158]}\n - item_input (input) params={\"shape\":[1,108]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,158]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,108]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":158,\"outFeatures\":434}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":434,\"outFeatures\":434}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":108,\"outFeatures\":434}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":434,\"outFeatures\":434}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":868,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (109-feature input, 37 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2249\nComponents:\n - input (input) params={\"shape\":[1,109]}\n - fc1 (linear) params={\"inFeatures\":109,\"outFeatures\":14}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":14,\"outFeatures\":14}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":14,\"outFeatures\":37}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":109,\"outFeatures\":754}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":754,\"outFeatures\":754}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":754,\"outFeatures\":37}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 334-feature input with 108 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2250\nComponents:\n - input (input) params={\"shape\":[1,334]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,334]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":334,\"outFeatures\":438}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":438,\"outFeatures\":971}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":971,\"outFeatures\":131}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":131,\"outFeatures\":890}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":890,\"outFeatures\":67}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":67,\"outFeatures\":559}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":559,\"outFeatures\":108}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1055-dim input: encode down to a 118-dim bottleneck and decode back to 1055. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2251\nComponents:\n - input (input) params={\"shape\":[1,1055]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1055]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1055,\"outFeatures\":759}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":759,\"outFeatures\":118}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":118,\"outFeatures\":759}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":759,\"outFeatures\":1055}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x43x43 image with 94 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2252\nComponents:\n - input (input) params={\"shape\":[1,3,43,43]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,43,43]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":19,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":19,\"outChannels\":42,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":42,\"outChannels\":47,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":47,\"outFeatures\":94}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 131-token sequences with 3 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2253\nComponents:\n - input (input) params={\"shape\":[1,131]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,131]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":45439,\"embeddingDim\":116}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":116,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":116,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":116,\"outFeatures\":3}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 371-token sequences with 8 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2254\nComponents:\n - input (input) params={\"shape\":[1,371]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,371]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":9775,\"embeddingDim\":720}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":720,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[720]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":720,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[720]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":720,\"outFeatures\":8}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 3245-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2256\nComponents:\n - input (input) params={\"shape\":[1,44]}\n - fc1 (linear) params={\"inFeatures\":44,\"outFeatures\":3245}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3245,\"outFeatures\":3245}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3245,\"outFeatures\":3245}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":3245,\"outFeatures\":2}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":44,\"outFeatures\":82}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":82,\"outFeatures\":82}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":82,\"outFeatures\":82}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":82,\"outFeatures\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 90-feature, 61-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2257\nComponents:\n - input (input) params={\"shape\":[1,90]}\n - fc1 (linear) params={\"inFeatures\":90,\"outFeatures\":37}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":37,\"outFeatures\":415}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":415,\"outFeatures\":451}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":451,\"outFeatures\":61}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":37}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":415}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":451}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 232-feature user input and a 247-feature item input, each through its own 2-layer MLP tower ending at width 325, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2258\nComponents:\n - user_input (input) params={\"shape\":[1,232]}\n - item_input (input) params={\"shape\":[1,247]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,232]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,247]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":232,\"outFeatures\":325}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":325,\"outFeatures\":325}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":247,\"outFeatures\":325}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":325,\"outFeatures\":325}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":650,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (117-feature input, 11 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2259\nComponents:\n - input (input) params={\"shape\":[1,117]}\n - fc1 (linear) params={\"inFeatures\":117,\"outFeatures\":12}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":12,\"outFeatures\":12}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":12,\"outFeatures\":11}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":117,\"outFeatures\":841}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":841,\"outFeatures\":841}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":841,\"outFeatures\":11}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 242-feature input with 67 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2260\nComponents:\n - input (input) params={\"shape\":[1,242]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,242]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":242,\"outFeatures\":608}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":608,\"outFeatures\":569}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":569,\"outFeatures\":970}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":970,\"outFeatures\":701}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":701,\"outFeatures\":67}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1779-dim input: encode down to a 118-dim bottleneck and decode back to 1779. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2261\nComponents:\n - input (input) params={\"shape\":[1,1779]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1779]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1779,\"outFeatures\":791}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":791,\"outFeatures\":118}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":118,\"outFeatures\":791}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":791,\"outFeatures\":1779}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x56x56 image with 57 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2262\nComponents:\n - input (input) params={\"shape\":[1,3,56,56]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,56,56]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":19,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":19,\"outChannels\":14,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":14,\"outChannels\":42,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":42,\"outFeatures\":57}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 312-token sequences with 48 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2263\nComponents:\n - input (input) params={\"shape\":[1,312]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,312]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":29301,\"embeddingDim\":456}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":456,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":456,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":456,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":456,\"outFeatures\":48}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 140-token sequences with 13 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2264\nComponents:\n - input (input) params={\"shape\":[1,140]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,140]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":45209,\"embeddingDim\":656}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":656,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[656]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":656,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[656]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":656,\"outFeatures\":13}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (250) is not divisible by numHeads (7). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-2265\nComponents:\n - input (input) params={\"shape\":[1,116]}\n - embed (embedding) params={\"numEmbeddings\":32596,\"embeddingDim\":250}\n - attn (multiHeadAttention) params={\"embedDim\":250,\"numHeads\":7}\n - head (linear) params={\"inFeatures\":250,\"outFeatures\":87}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 3745-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2266\nComponents:\n - input (input) params={\"shape\":[1,217]}\n - fc1 (linear) params={\"inFeatures\":217,\"outFeatures\":3745}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3745,\"outFeatures\":3745}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":3745,\"outFeatures\":32}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":217,\"outFeatures\":137}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":137,\"outFeatures\":137}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":137,\"outFeatures\":32}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 228-feature, 56-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2267\nComponents:\n - input (input) params={\"shape\":[1,228]}\n - fc1 (linear) params={\"inFeatures\":228,\"outFeatures\":112}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":112,\"outFeatures\":482}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":482,\"outFeatures\":90}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":90,\"outFeatures\":103}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":103,\"outFeatures\":56}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":112}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":482}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":90}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":103}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 233-feature user input and a 189-feature item input, each through its own 2-layer MLP tower ending at width 224, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2268\nComponents:\n - user_input (input) params={\"shape\":[1,233]}\n - item_input (input) params={\"shape\":[1,189]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,233]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,189]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":233,\"outFeatures\":224}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":224,\"outFeatures\":224}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":189,\"outFeatures\":224}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":224,\"outFeatures\":224}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":448,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (121-feature input, 25 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2269\nComponents:\n - input (input) params={\"shape\":[1,121]}\n - fc1 (linear) params={\"inFeatures\":121,\"outFeatures\":17}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":17,\"outFeatures\":17}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":17,\"outFeatures\":25}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":121,\"outFeatures\":908}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":908,\"outFeatures\":908}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":908,\"outFeatures\":25}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 345-feature input with 124 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2270\nComponents:\n - input (input) params={\"shape\":[1,345]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,345]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":345,\"outFeatures\":926}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":926,\"outFeatures\":951}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":951,\"outFeatures\":357}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":357,\"outFeatures\":124}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1899-dim input: encode down to a 145-dim bottleneck and decode back to 1899. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2271\nComponents:\n - input (input) params={\"shape\":[1,1899]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1899]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1899,\"outFeatures\":440}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":440,\"outFeatures\":145}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":145,\"outFeatures\":440}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":440,\"outFeatures\":1899}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x64x64 image with 97 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2272\nComponents:\n - input (input) params={\"shape\":[1,3,64,64]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,64,64]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":17,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":17,\"outChannels\":15,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":15,\"outChannels\":29,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":29,\"outChannels\":16,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":16,\"outFeatures\":97}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 45-token sequences with 65 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2273\nComponents:\n - input (input) params={\"shape\":[1,45]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,45]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":21833,\"embeddingDim\":392}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":392,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":392,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":392,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":392,\"outFeatures\":65}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 512-token sequences with 96 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2274\nComponents:\n - input (input) params={\"shape\":[1,512]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,512]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":8170,\"embeddingDim\":188}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":188,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[188]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":188,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[188]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":188,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[188]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":188,\"outFeatures\":96}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (70) is not divisible by numHeads (11). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-2275\nComponents:\n - input (input) params={\"shape\":[1,310]}\n - embed (embedding) params={\"numEmbeddings\":45665,\"embeddingDim\":70}\n - attn (multiHeadAttention) params={\"embedDim\":70,\"numHeads\":11}\n - head (linear) params={\"inFeatures\":70,\"outFeatures\":73}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 3388-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2276\nComponents:\n - input (input) params={\"shape\":[1,183]}\n - fc1 (linear) params={\"inFeatures\":183,\"outFeatures\":3388}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3388,\"outFeatures\":3388}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":3388,\"outFeatures\":4}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":183,\"outFeatures\":259}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":259,\"outFeatures\":259}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":259,\"outFeatures\":4}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 164-feature, 62-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2277\nComponents:\n - input (input) params={\"shape\":[1,164]}\n - fc1 (linear) params={\"inFeatures\":164,\"outFeatures\":238}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":238,\"outFeatures\":341}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":341,\"outFeatures\":34}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":34,\"outFeatures\":106}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":106,\"outFeatures\":273}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":273,\"outFeatures\":62}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":238}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":341}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":34}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":106}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":273}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 93-feature user input and a 103-feature item input, each through its own 2-layer MLP tower ending at width 429, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2278\nComponents:\n - user_input (input) params={\"shape\":[1,93]}\n - item_input (input) params={\"shape\":[1,103]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,93]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,103]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":93,\"outFeatures\":429}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":429,\"outFeatures\":429}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":103,\"outFeatures\":429}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":429,\"outFeatures\":429}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":858,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (56-feature input, 33 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2279\nComponents:\n - input (input) params={\"shape\":[1,56]}\n - fc1 (linear) params={\"inFeatures\":56,\"outFeatures\":20}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":20,\"outFeatures\":20}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":20,\"outFeatures\":33}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":56,\"outFeatures\":686}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":686,\"outFeatures\":686}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":686,\"outFeatures\":33}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 297-feature input with 33 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2280\nComponents:\n - input (input) params={\"shape\":[1,297]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,297]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":297,\"outFeatures\":340}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":340,\"outFeatures\":616}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":616,\"outFeatures\":938}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":938,\"outFeatures\":414}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":414,\"outFeatures\":33}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 848-dim input: encode down to a 95-dim bottleneck and decode back to 848. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2281\nComponents:\n - input (input) params={\"shape\":[1,848]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,848]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":848,\"outFeatures\":204}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":204,\"outFeatures\":95}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":95,\"outFeatures\":204}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":204,\"outFeatures\":848}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x61x61 image with 8 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2282\nComponents:\n - input (input) params={\"shape\":[1,3,61,61]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,61,61]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":58,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":58,\"outChannels\":38,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":38,\"outChannels\":52,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":52,\"outFeatures\":8}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 340-token sequences with 78 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2283\nComponents:\n - input (input) params={\"shape\":[1,340]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,340]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":26440,\"embeddingDim\":176}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":176,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":176,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":176,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":176,\"outFeatures\":78}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 484-token sequences with 17 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2284\nComponents:\n - input (input) params={\"shape\":[1,484]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,484]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":12742,\"embeddingDim\":152}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":152,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[152]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":152,\"outFeatures\":17}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (346) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-2285\nComponents:\n - input (input) params={\"shape\":[1,229]}\n - embed (embedding) params={\"numEmbeddings\":12427,\"embeddingDim\":346}\n - attn (multiHeadAttention) params={\"embedDim\":346,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":346,\"outFeatures\":70}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 3352-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2286\nComponents:\n - input (input) params={\"shape\":[1,140]}\n - fc1 (linear) params={\"inFeatures\":140,\"outFeatures\":3352}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3352,\"outFeatures\":3352}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":3352,\"outFeatures\":9}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":140,\"outFeatures\":68}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":68,\"outFeatures\":68}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":68,\"outFeatures\":9}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 206-feature, 61-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2287\nComponents:\n - input (input) params={\"shape\":[1,206]}\n - fc1 (linear) params={\"inFeatures\":206,\"outFeatures\":246}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":246,\"outFeatures\":444}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":444,\"outFeatures\":284}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":284,\"outFeatures\":61}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":246}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":444}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":284}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 246-feature user input and a 25-feature item input, each through its own 2-layer MLP tower ending at width 113, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2288\nComponents:\n - user_input (input) params={\"shape\":[1,246]}\n - item_input (input) params={\"shape\":[1,25]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,246]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,25]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":246,\"outFeatures\":113}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":113,\"outFeatures\":113}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":25,\"outFeatures\":113}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":113,\"outFeatures\":113}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":226,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (37-feature input, 49 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2289\nComponents:\n - input (input) params={\"shape\":[1,37]}\n - fc1 (linear) params={\"inFeatures\":37,\"outFeatures\":16}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":16,\"outFeatures\":16}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":16,\"outFeatures\":49}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":37,\"outFeatures\":922}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":922,\"outFeatures\":922}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":922,\"outFeatures\":49}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 342-feature input with 92 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2290\nComponents:\n - input (input) params={\"shape\":[1,342]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,342]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":342,\"outFeatures\":832}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":832,\"outFeatures\":669}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":669,\"outFeatures\":69}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":69,\"outFeatures\":92}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 993-dim input: encode down to a 104-dim bottleneck and decode back to 993. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2291\nComponents:\n - input (input) params={\"shape\":[1,993]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,993]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":993,\"outFeatures\":295}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":295,\"outFeatures\":104}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":104,\"outFeatures\":295}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":295,\"outFeatures\":993}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x28x28 image with 93 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2292\nComponents:\n - input (input) params={\"shape\":[1,3,28,28]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,28,28]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":13,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":13,\"outChannels\":25,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":25,\"outChannels\":26,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":26,\"outFeatures\":93}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 443-token sequences with 70 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2293\nComponents:\n - input (input) params={\"shape\":[1,443]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,443]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":11639,\"embeddingDim\":106}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":106,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":106,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":106,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":106,\"outFeatures\":70}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 365-token sequences with 29 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2294\nComponents:\n - input (input) params={\"shape\":[1,365]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,365]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":9596,\"embeddingDim\":360}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":360,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[360]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":360,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[360]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":360,\"outFeatures\":29}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 2028-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2296\nComponents:\n - input (input) params={\"shape\":[1,190]}\n - fc1 (linear) params={\"inFeatures\":190,\"outFeatures\":2028}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2028,\"outFeatures\":2028}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2028,\"outFeatures\":2028}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":2028,\"outFeatures\":18}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":190,\"outFeatures\":314}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":314,\"outFeatures\":314}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":314,\"outFeatures\":314}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":314,\"outFeatures\":18}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 151-feature, 69-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2297\nComponents:\n - input (input) params={\"shape\":[1,151]}\n - fc1 (linear) params={\"inFeatures\":151,\"outFeatures\":318}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":318,\"outFeatures\":93}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":93,\"outFeatures\":324}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":324,\"outFeatures\":292}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":292,\"outFeatures\":69}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":318}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":93}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":324}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":292}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 125-feature user input and a 158-feature item input, each through its own 2-layer MLP tower ending at width 63, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2298\nComponents:\n - user_input (input) params={\"shape\":[1,125]}\n - item_input (input) params={\"shape\":[1,158]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,125]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,158]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":125,\"outFeatures\":63}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":63,\"outFeatures\":63}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":158,\"outFeatures\":63}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":63,\"outFeatures\":63}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":126,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (64-feature input, 12 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2299\nComponents:\n - input (input) params={\"shape\":[1,64]}\n - fc1 (linear) params={\"inFeatures\":64,\"outFeatures\":5}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":5,\"outFeatures\":5}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":5,\"outFeatures\":12}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":64,\"outFeatures\":1340}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1340,\"outFeatures\":1340}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1340,\"outFeatures\":12}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 396-feature input with 178 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2300\nComponents:\n - input (input) params={\"shape\":[1,396]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,396]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":396,\"outFeatures\":104}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":104,\"outFeatures\":238}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":238,\"outFeatures\":130}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":130,\"outFeatures\":314}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":314,\"outFeatures\":115}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":115,\"outFeatures\":258}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":258,\"outFeatures\":178}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 597-dim input: encode down to a 144-dim bottleneck and decode back to 597. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2301\nComponents:\n - input (input) params={\"shape\":[1,597]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,597]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":597,\"outFeatures\":155}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":155,\"outFeatures\":144}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":144,\"outFeatures\":155}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":155,\"outFeatures\":597}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x43x43 image with 68 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2302\nComponents:\n - input (input) params={\"shape\":[1,3,43,43]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,43,43]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":31,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":31,\"outChannels\":46,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":46,\"outChannels\":33,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":33,\"outChannels\":59,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":59,\"outFeatures\":68}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 350-token sequences with 98 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2303\nComponents:\n - input (input) params={\"shape\":[1,350]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,350]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":22903,\"embeddingDim\":488}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":488,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":488,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":488,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":488,\"outFeatures\":98}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 39-token sequences with 27 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2304\nComponents:\n - input (input) params={\"shape\":[1,39]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,39]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":17702,\"embeddingDim\":176}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":176,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[176]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":176,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[176]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":176,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[176]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":176,\"outFeatures\":27}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 3353-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2306\nComponents:\n - input (input) params={\"shape\":[1,209]}\n - fc1 (linear) params={\"inFeatures\":209,\"outFeatures\":3353}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3353,\"outFeatures\":3353}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3353,\"outFeatures\":3353}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":3353,\"outFeatures\":41}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":209,\"outFeatures\":274}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":274,\"outFeatures\":274}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":274,\"outFeatures\":274}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":274,\"outFeatures\":41}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 173-feature, 54-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2307\nComponents:\n - input (input) params={\"shape\":[1,173]}\n - fc1 (linear) params={\"inFeatures\":173,\"outFeatures\":64}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":64,\"outFeatures\":511}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":511,\"outFeatures\":281}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":281,\"outFeatures\":69}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":69,\"outFeatures\":83}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":83,\"outFeatures\":54}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":64}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":511}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":281}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":69}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":83}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 166-feature user input and a 170-feature item input, each through its own 2-layer MLP tower ending at width 343, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2308\nComponents:\n - user_input (input) params={\"shape\":[1,166]}\n - item_input (input) params={\"shape\":[1,170]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,166]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,170]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":166,\"outFeatures\":343}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":343,\"outFeatures\":343}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":170,\"outFeatures\":343}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":343,\"outFeatures\":343}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":686,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (128-feature input, 6 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2309\nComponents:\n - input (input) params={\"shape\":[1,128]}\n - fc1 (linear) params={\"inFeatures\":128,\"outFeatures\":12}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":12,\"outFeatures\":12}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":12,\"outFeatures\":6}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":128,\"outFeatures\":1154}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1154,\"outFeatures\":1154}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1154,\"outFeatures\":6}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 110-feature input with 168 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2310\nComponents:\n - input (input) params={\"shape\":[1,110]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,110]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":110,\"outFeatures\":897}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":897,\"outFeatures\":537}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":537,\"outFeatures\":749}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":749,\"outFeatures\":757}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":757,\"outFeatures\":652}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":652,\"outFeatures\":743}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":743,\"outFeatures\":168}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 922-dim input: encode down to a 132-dim bottleneck and decode back to 922. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2311\nComponents:\n - input (input) params={\"shape\":[1,922]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,922]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":922,\"outFeatures\":922}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":922,\"outFeatures\":132}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":132,\"outFeatures\":922}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":922,\"outFeatures\":922}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x31x31 image with 70 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2312\nComponents:\n - input (input) params={\"shape\":[1,3,31,31]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,31,31]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":63,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":63,\"outChannels\":52,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":52,\"outChannels\":34,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":34,\"outChannels\":42,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":42,\"outFeatures\":70}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 382-token sequences with 75 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2313\nComponents:\n - input (input) params={\"shape\":[1,382]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,382]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":8936,\"embeddingDim\":118}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":118,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":118,\"outFeatures\":75}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 173-token sequences with 51 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2314\nComponents:\n - input (input) params={\"shape\":[1,173]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,173]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":26777,\"embeddingDim\":272}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":272,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[272]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":272,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[272]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":272,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[272]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":272,\"outFeatures\":51}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (184) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-2315\nComponents:\n - input (input) params={\"shape\":[1,501]}\n - embed (embedding) params={\"numEmbeddings\":28750,\"embeddingDim\":184}\n - attn (multiHeadAttention) params={\"embedDim\":184,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":184,\"outFeatures\":2}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":8}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 3499-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2316\nComponents:\n - input (input) params={\"shape\":[1,183]}\n - fc1 (linear) params={\"inFeatures\":183,\"outFeatures\":3499}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3499,\"outFeatures\":3499}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":3499,\"outFeatures\":31}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":183,\"outFeatures\":342}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":342,\"outFeatures\":342}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":342,\"outFeatures\":31}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 193-feature, 29-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2317\nComponents:\n - input (input) params={\"shape\":[1,193]}\n - fc1 (linear) params={\"inFeatures\":193,\"outFeatures\":411}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":411,\"outFeatures\":197}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":197,\"outFeatures\":241}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":241,\"outFeatures\":356}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":356,\"outFeatures\":353}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":353,\"outFeatures\":29}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":411}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":197}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":241}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":356}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":353}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 204-feature user input and a 250-feature item input, each through its own 2-layer MLP tower ending at width 82, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2318\nComponents:\n - user_input (input) params={\"shape\":[1,204]}\n - item_input (input) params={\"shape\":[1,250]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,204]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,250]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":204,\"outFeatures\":82}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":82,\"outFeatures\":82}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":250,\"outFeatures\":82}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":82,\"outFeatures\":82}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":164,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (90-feature input, 43 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2319\nComponents:\n - input (input) params={\"shape\":[1,90]}\n - fc1 (linear) params={\"inFeatures\":90,\"outFeatures\":22}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":22,\"outFeatures\":22}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":22,\"outFeatures\":43}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":90,\"outFeatures\":813}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":813,\"outFeatures\":813}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":813,\"outFeatures\":43}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 267-feature input with 128 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2320\nComponents:\n - input (input) params={\"shape\":[1,267]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,267]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":267,\"outFeatures\":813}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":813,\"outFeatures\":1010}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":1010,\"outFeatures\":128}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1740-dim input: encode down to a 158-dim bottleneck and decode back to 1740. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2321\nComponents:\n - input (input) params={\"shape\":[1,1740]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1740]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1740,\"outFeatures\":1012}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":1012,\"outFeatures\":158}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":158,\"outFeatures\":1012}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":1012,\"outFeatures\":1740}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x61x61 image with 44 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2322\nComponents:\n - input (input) params={\"shape\":[1,3,61,61]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,61,61]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":40,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":40,\"outChannels\":19,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":19,\"outChannels\":8,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":8,\"outChannels\":59,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":59,\"outFeatures\":44}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 139-token sequences with 76 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2323\nComponents:\n - input (input) params={\"shape\":[1,139]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,139]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":31751,\"embeddingDim\":456}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":456,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":456,\"outFeatures\":76}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 240-token sequences with 59 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2324\nComponents:\n - input (input) params={\"shape\":[1,240]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,240]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":17238,\"embeddingDim\":60}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":60,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[60]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":60,\"outFeatures\":59}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 2247-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2326\nComponents:\n - input (input) params={\"shape\":[1,156]}\n - fc1 (linear) params={\"inFeatures\":156,\"outFeatures\":2247}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2247,\"outFeatures\":2247}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":2247,\"outFeatures\":22}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":156,\"outFeatures\":171}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":171,\"outFeatures\":171}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":171,\"outFeatures\":22}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 118-feature, 60-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2327\nComponents:\n - input (input) params={\"shape\":[1,118]}\n - fc1 (linear) params={\"inFeatures\":118,\"outFeatures\":435}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":435,\"outFeatures\":129}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":129,\"outFeatures\":491}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":491,\"outFeatures\":46}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":46,\"outFeatures\":394}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":394,\"outFeatures\":60}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":435}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":129}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":491}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":46}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":394}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 142-feature user input and a 238-feature item input, each through its own 2-layer MLP tower ending at width 425, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2328\nComponents:\n - user_input (input) params={\"shape\":[1,142]}\n - item_input (input) params={\"shape\":[1,238]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,142]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,238]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":142,\"outFeatures\":425}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":425,\"outFeatures\":425}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":238,\"outFeatures\":425}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":425,\"outFeatures\":425}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":850,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (70-feature input, 50 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2329\nComponents:\n - input (input) params={\"shape\":[1,70]}\n - fc1 (linear) params={\"inFeatures\":70,\"outFeatures\":22}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":22,\"outFeatures\":22}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":22,\"outFeatures\":50}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":70,\"outFeatures\":734}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":734,\"outFeatures\":734}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":734,\"outFeatures\":50}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 12-feature input with 184 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2330\nComponents:\n - input (input) params={\"shape\":[1,12]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,12]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":12,\"outFeatures\":755}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":755,\"outFeatures\":845}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":845,\"outFeatures\":559}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":559,\"outFeatures\":184}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1978-dim input: encode down to a 17-dim bottleneck and decode back to 1978. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2331\nComponents:\n - input (input) params={\"shape\":[1,1978]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1978]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1978,\"outFeatures\":930}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":930,\"outFeatures\":17}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":17,\"outFeatures\":930}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":930,\"outFeatures\":1978}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x51x51 image with 22 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2332\nComponents:\n - input (input) params={\"shape\":[1,3,51,51]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,51,51]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":36,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":36,\"outChannels\":8,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":8,\"outChannels\":36,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":36,\"outChannels\":64,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":64,\"outFeatures\":22}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 119-token sequences with 50 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2333\nComponents:\n - input (input) params={\"shape\":[1,119]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,119]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":45544,\"embeddingDim\":400}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":400,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":400,\"outFeatures\":50}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 455-token sequences with 31 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2334\nComponents:\n - input (input) params={\"shape\":[1,455]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,455]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":38995,\"embeddingDim\":80}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":80,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[80]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":80,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[80]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":80,\"outFeatures\":31}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 1841-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2336\nComponents:\n - input (input) params={\"shape\":[1,128]}\n - fc1 (linear) params={\"inFeatures\":128,\"outFeatures\":1841}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":1841,\"outFeatures\":1841}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":1841,\"outFeatures\":1841}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":1841,\"outFeatures\":1841}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":1841,\"outFeatures\":42}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":128,\"outFeatures\":345}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":345,\"outFeatures\":345}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":345,\"outFeatures\":345}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":345,\"outFeatures\":345}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":345,\"outFeatures\":42}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 49-feature, 37-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2337\nComponents:\n - input (input) params={\"shape\":[1,49]}\n - fc1 (linear) params={\"inFeatures\":49,\"outFeatures\":392}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":392,\"outFeatures\":410}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":410,\"outFeatures\":286}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":286,\"outFeatures\":37}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":392}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":410}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":286}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 208-feature user input and a 239-feature item input, each through its own 2-layer MLP tower ending at width 178, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2338\nComponents:\n - user_input (input) params={\"shape\":[1,208]}\n - item_input (input) params={\"shape\":[1,239]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,208]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,239]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":208,\"outFeatures\":178}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":178,\"outFeatures\":178}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":239,\"outFeatures\":178}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":178,\"outFeatures\":178}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":356,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (17-feature input, 7 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2339\nComponents:\n - input (input) params={\"shape\":[1,17]}\n - fc1 (linear) params={\"inFeatures\":17,\"outFeatures\":8}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":8,\"outFeatures\":8}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":8,\"outFeatures\":7}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":17,\"outFeatures\":1159}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1159,\"outFeatures\":1159}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1159,\"outFeatures\":7}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 433-feature input with 83 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2340\nComponents:\n - input (input) params={\"shape\":[1,433]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,433]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":433,\"outFeatures\":543}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":543,\"outFeatures\":603}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":603,\"outFeatures\":157}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":157,\"outFeatures\":715}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":715,\"outFeatures\":88}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":88,\"outFeatures\":352}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":352,\"outFeatures\":83}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 196-dim input: encode down to a 34-dim bottleneck and decode back to 196. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2341\nComponents:\n - input (input) params={\"shape\":[1,196]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,196]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":196,\"outFeatures\":275}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":275,\"outFeatures\":34}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":34,\"outFeatures\":275}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":275,\"outFeatures\":196}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x59x59 image with 58 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2342\nComponents:\n - input (input) params={\"shape\":[1,3,59,59]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,59,59]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":38,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":38,\"outChannels\":39,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":39,\"outChannels\":63,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":63,\"outChannels\":31,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":31,\"outFeatures\":58}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 212-token sequences with 32 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2343\nComponents:\n - input (input) params={\"shape\":[1,212]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,212]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":13735,\"embeddingDim\":200}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":200,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":200,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":200,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":200,\"outFeatures\":32}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 379-token sequences with 86 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2344\nComponents:\n - input (input) params={\"shape\":[1,379]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,379]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":17241,\"embeddingDim\":512}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":512,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[512]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":512,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[512]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":512,\"outFeatures\":86}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (88) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-2345\nComponents:\n - input (input) params={\"shape\":[1,191]}\n - embed (embedding) params={\"numEmbeddings\":33065,\"embeddingDim\":88}\n - attn (multiHeadAttention) params={\"embedDim\":88,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":88,\"outFeatures\":64}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":8}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 1576-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2346\nComponents:\n - input (input) params={\"shape\":[1,65]}\n - fc1 (linear) params={\"inFeatures\":65,\"outFeatures\":1576}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":1576,\"outFeatures\":1576}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":1576,\"outFeatures\":1576}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":1576,\"outFeatures\":39}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":65,\"outFeatures\":231}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":231,\"outFeatures\":231}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":231,\"outFeatures\":231}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":231,\"outFeatures\":39}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 52-feature, 33-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2347\nComponents:\n - input (input) params={\"shape\":[1,52]}\n - fc1 (linear) params={\"inFeatures\":52,\"outFeatures\":123}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":123,\"outFeatures\":364}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":364,\"outFeatures\":455}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":455,\"outFeatures\":33}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":123}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":364}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":455}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 163-feature user input and a 205-feature item input, each through its own 2-layer MLP tower ending at width 94, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2348\nComponents:\n - user_input (input) params={\"shape\":[1,163]}\n - item_input (input) params={\"shape\":[1,205]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,163]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,205]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":163,\"outFeatures\":94}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":94,\"outFeatures\":94}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":205,\"outFeatures\":94}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":94,\"outFeatures\":94}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":188,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (55-feature input, 35 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2349\nComponents:\n - input (input) params={\"shape\":[1,55]}\n - fc1 (linear) params={\"inFeatures\":55,\"outFeatures\":21}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":21,\"outFeatures\":21}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":21,\"outFeatures\":35}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":55,\"outFeatures\":705}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":705,\"outFeatures\":705}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":705,\"outFeatures\":35}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 485-feature input with 167 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2350\nComponents:\n - input (input) params={\"shape\":[1,485]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,485]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":485,\"outFeatures\":232}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":232,\"outFeatures\":232}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":232,\"outFeatures\":167}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1916-dim input: encode down to a 32-dim bottleneck and decode back to 1916. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2351\nComponents:\n - input (input) params={\"shape\":[1,1916]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1916]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1916,\"outFeatures\":458}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":458,\"outFeatures\":32}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":32,\"outFeatures\":458}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":458,\"outFeatures\":1916}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x33x33 image with 90 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2352\nComponents:\n - input (input) params={\"shape\":[1,3,33,33]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,33,33]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":27,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":27,\"outChannels\":28,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":28,\"outFeatures\":90}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 91-token sequences with 55 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2353\nComponents:\n - input (input) params={\"shape\":[1,91]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,91]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":12081,\"embeddingDim\":80}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":80,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":80,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":80,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":80,\"outFeatures\":55}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 490-token sequences with 47 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2354\nComponents:\n - input (input) params={\"shape\":[1,490]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,490]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":48282,\"embeddingDim\":592}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":592,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[592]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":592,\"outFeatures\":47}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (248) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-2355\nComponents:\n - input (input) params={\"shape\":[1,378]}\n - embed (embedding) params={\"numEmbeddings\":40211,\"embeddingDim\":248}\n - attn (multiHeadAttention) params={\"embedDim\":248,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":248,\"outFeatures\":78}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":8}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 1991-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2356\nComponents:\n - input (input) params={\"shape\":[1,253]}\n - fc1 (linear) params={\"inFeatures\":253,\"outFeatures\":1991}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":1991,\"outFeatures\":1991}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":1991,\"outFeatures\":37}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":253,\"outFeatures\":214}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":214,\"outFeatures\":214}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":214,\"outFeatures\":37}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 190-feature, 39-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2357\nComponents:\n - input (input) params={\"shape\":[1,190]}\n - fc1 (linear) params={\"inFeatures\":190,\"outFeatures\":304}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":304,\"outFeatures\":301}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":301,\"outFeatures\":409}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":409,\"outFeatures\":39}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":304}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":301}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":409}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 147-feature user input and a 154-feature item input, each through its own 2-layer MLP tower ending at width 177, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2358\nComponents:\n - user_input (input) params={\"shape\":[1,147]}\n - item_input (input) params={\"shape\":[1,154]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,147]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,154]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":147,\"outFeatures\":177}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":177,\"outFeatures\":177}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":154,\"outFeatures\":177}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":177,\"outFeatures\":177}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":354,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (63-feature input, 36 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2359\nComponents:\n - input (input) params={\"shape\":[1,63]}\n - fc1 (linear) params={\"inFeatures\":63,\"outFeatures\":4}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":4,\"outFeatures\":4}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":4,\"outFeatures\":36}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":63,\"outFeatures\":1343}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1343,\"outFeatures\":1343}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1343,\"outFeatures\":36}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 141-feature input with 22 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2360\nComponents:\n - input (input) params={\"shape\":[1,141]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,141]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":141,\"outFeatures\":680}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":680,\"outFeatures\":697}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":697,\"outFeatures\":22}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 295-dim input: encode down to a 60-dim bottleneck and decode back to 295. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2361\nComponents:\n - input (input) params={\"shape\":[1,295]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,295]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":295,\"outFeatures\":339}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":339,\"outFeatures\":60}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":60,\"outFeatures\":339}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":339,\"outFeatures\":295}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x39x39 image with 25 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2362\nComponents:\n - input (input) params={\"shape\":[1,3,39,39]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,39,39]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":21,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":21,\"outChannels\":15,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":15,\"outChannels\":53,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":53,\"outChannels\":30,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":30,\"outFeatures\":25}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 244-token sequences with 62 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2363\nComponents:\n - input (input) params={\"shape\":[1,244]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,244]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":44665,\"embeddingDim\":228}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":228,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":228,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":228,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":228,\"outFeatures\":62}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 424-token sequences with 97 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2364\nComponents:\n - input (input) params={\"shape\":[1,424]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,424]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":11096,\"embeddingDim\":480}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":480,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[480]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":480,\"outFeatures\":97}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 1622-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2366\nComponents:\n - input (input) params={\"shape\":[1,184]}\n - fc1 (linear) params={\"inFeatures\":184,\"outFeatures\":1622}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":1622,\"outFeatures\":1622}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":1622,\"outFeatures\":20}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":184,\"outFeatures\":96}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":96,\"outFeatures\":96}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":96,\"outFeatures\":20}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 155-feature, 62-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2367\nComponents:\n - input (input) params={\"shape\":[1,155]}\n - fc1 (linear) params={\"inFeatures\":155,\"outFeatures\":91}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":91,\"outFeatures\":66}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":66,\"outFeatures\":357}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":357,\"outFeatures\":62}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":91}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":66}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":357}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 252-feature user input and a 96-feature item input, each through its own 2-layer MLP tower ending at width 237, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2368\nComponents:\n - user_input (input) params={\"shape\":[1,252]}\n - item_input (input) params={\"shape\":[1,96]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,252]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,96]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":252,\"outFeatures\":237}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":237,\"outFeatures\":237}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":96,\"outFeatures\":237}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":237,\"outFeatures\":237}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":474,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (90-feature input, 49 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2369\nComponents:\n - input (input) params={\"shape\":[1,90]}\n - fc1 (linear) params={\"inFeatures\":90,\"outFeatures\":17}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":17,\"outFeatures\":17}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":17,\"outFeatures\":49}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":90,\"outFeatures\":844}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":844,\"outFeatures\":844}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":844,\"outFeatures\":49}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 19-feature input with 171 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2370\nComponents:\n - input (input) params={\"shape\":[1,19]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,19]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":19,\"outFeatures\":807}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":807,\"outFeatures\":261}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":261,\"outFeatures\":38}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":38,\"outFeatures\":171}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1174-dim input: encode down to a 45-dim bottleneck and decode back to 1174. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2371\nComponents:\n - input (input) params={\"shape\":[1,1174]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1174]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1174,\"outFeatures\":486}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":486,\"outFeatures\":45}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":45,\"outFeatures\":486}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":486,\"outFeatures\":1174}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x55x55 image with 55 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2372\nComponents:\n - input (input) params={\"shape\":[1,3,55,55]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,55,55]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":17,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":17,\"outChannels\":11,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":11,\"outChannels\":23,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":23,\"outFeatures\":55}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 143-token sequences with 70 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2373\nComponents:\n - input (input) params={\"shape\":[1,143]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,143]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":15698,\"embeddingDim\":244}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":244,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":244,\"outFeatures\":70}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 300-token sequences with 19 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2374\nComponents:\n - input (input) params={\"shape\":[1,300]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,300]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":9549,\"embeddingDim\":112}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":112,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[112]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":112,\"outFeatures\":19}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (480) is not divisible by numHeads (7). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-2375\nComponents:\n - input (input) params={\"shape\":[1,150]}\n - embed (embedding) params={\"numEmbeddings\":37579,\"embeddingDim\":480}\n - attn (multiHeadAttention) params={\"embedDim\":480,\"numHeads\":7}\n - head (linear) params={\"inFeatures\":480,\"outFeatures\":85}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":16}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3081-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2376\nComponents:\n - input (input) params={\"shape\":[1,139]}\n - fc1 (linear) params={\"inFeatures\":139,\"outFeatures\":3081}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3081,\"outFeatures\":3081}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3081,\"outFeatures\":3081}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3081,\"outFeatures\":3081}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3081,\"outFeatures\":17}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":139,\"outFeatures\":162}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":162,\"outFeatures\":162}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":162,\"outFeatures\":162}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":162,\"outFeatures\":162}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":162,\"outFeatures\":17}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 158-feature, 74-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2377\nComponents:\n - input (input) params={\"shape\":[1,158]}\n - fc1 (linear) params={\"inFeatures\":158,\"outFeatures\":299}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":299,\"outFeatures\":244}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":244,\"outFeatures\":205}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":205,\"outFeatures\":74}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":299}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":244}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":205}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 79-feature user input and a 90-feature item input, each through its own 2-layer MLP tower ending at width 296, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2378\nComponents:\n - user_input (input) params={\"shape\":[1,79]}\n - item_input (input) params={\"shape\":[1,90]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,79]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,90]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":79,\"outFeatures\":296}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":296,\"outFeatures\":296}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":90,\"outFeatures\":296}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":296,\"outFeatures\":296}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":592,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (66-feature input, 22 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2379\nComponents:\n - input (input) params={\"shape\":[1,66]}\n - fc1 (linear) params={\"inFeatures\":66,\"outFeatures\":21}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":21,\"outFeatures\":21}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":21,\"outFeatures\":22}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":66,\"outFeatures\":687}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":687,\"outFeatures\":687}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":687,\"outFeatures\":22}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 238-feature input with 156 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2380\nComponents:\n - input (input) params={\"shape\":[1,238]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,238]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":238,\"outFeatures\":390}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":390,\"outFeatures\":36}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":36,\"outFeatures\":913}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":913,\"outFeatures\":156}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 532-dim input: encode down to a 175-dim bottleneck and decode back to 532. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2381\nComponents:\n - input (input) params={\"shape\":[1,532]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,532]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":532,\"outFeatures\":314}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":314,\"outFeatures\":175}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":175,\"outFeatures\":314}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":314,\"outFeatures\":532}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x32x32 image with 98 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2382\nComponents:\n - input (input) params={\"shape\":[1,3,32,32]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,32,32]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":33,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":33,\"outChannels\":49,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":49,\"outFeatures\":98}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 462-token sequences with 39 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2383\nComponents:\n - input (input) params={\"shape\":[1,462]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,462]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":43896,\"embeddingDim\":50}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":50,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":50,\"outFeatures\":39}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 309-token sequences with 41 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2384\nComponents:\n - input (input) params={\"shape\":[1,309]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,309]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":48433,\"embeddingDim\":92}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":92,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[92]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":92,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[92]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":92,\"outFeatures\":41}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 3448-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2386\nComponents:\n - input (input) params={\"shape\":[1,77]}\n - fc1 (linear) params={\"inFeatures\":77,\"outFeatures\":3448}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3448,\"outFeatures\":3448}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3448,\"outFeatures\":3448}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":3448,\"outFeatures\":47}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":77,\"outFeatures\":84}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":84,\"outFeatures\":84}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":84,\"outFeatures\":84}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":84,\"outFeatures\":47}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 194-feature, 90-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2387\nComponents:\n - input (input) params={\"shape\":[1,194]}\n - fc1 (linear) params={\"inFeatures\":194,\"outFeatures\":113}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":113,\"outFeatures\":232}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":232,\"outFeatures\":430}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":430,\"outFeatures\":90}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":113}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":232}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":430}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 32-feature user input and a 78-feature item input, each through its own 2-layer MLP tower ending at width 88, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2388\nComponents:\n - user_input (input) params={\"shape\":[1,32]}\n - item_input (input) params={\"shape\":[1,78]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,32]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,78]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":32,\"outFeatures\":88}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":88,\"outFeatures\":88}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":78,\"outFeatures\":88}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":88,\"outFeatures\":88}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":176,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (99-feature input, 39 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2389\nComponents:\n - input (input) params={\"shape\":[1,99]}\n - fc1 (linear) params={\"inFeatures\":99,\"outFeatures\":8}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":8,\"outFeatures\":8}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":8,\"outFeatures\":39}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":99,\"outFeatures\":1034}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1034,\"outFeatures\":1034}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1034,\"outFeatures\":39}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 82-feature input with 126 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2390\nComponents:\n - input (input) params={\"shape\":[1,82]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,82]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":82,\"outFeatures\":110}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":110,\"outFeatures\":485}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":485,\"outFeatures\":927}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":927,\"outFeatures\":693}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":693,\"outFeatures\":126}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1514-dim input: encode down to a 69-dim bottleneck and decode back to 1514. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2391\nComponents:\n - input (input) params={\"shape\":[1,1514]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1514]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1514,\"outFeatures\":944}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":944,\"outFeatures\":69}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":69,\"outFeatures\":944}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":944,\"outFeatures\":1514}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x53x53 image with 98 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2392\nComponents:\n - input (input) params={\"shape\":[1,3,53,53]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,53,53]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":43,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":43,\"outChannels\":32,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":32,\"outChannels\":30,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":30,\"outFeatures\":98}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 500-token sequences with 78 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2393\nComponents:\n - input (input) params={\"shape\":[1,500]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,500]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":19771,\"embeddingDim\":72}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":72,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":72,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":72,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":72,\"outFeatures\":78}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 449-token sequences with 43 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2394\nComponents:\n - input (input) params={\"shape\":[1,449]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,449]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":49125,\"embeddingDim\":496}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":496,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[496]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":496,\"outFeatures\":43}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 2453-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2396\nComponents:\n - input (input) params={\"shape\":[1,228]}\n - fc1 (linear) params={\"inFeatures\":228,\"outFeatures\":2453}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2453,\"outFeatures\":2453}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2453,\"outFeatures\":2453}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":2453,\"outFeatures\":2453}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":2453,\"outFeatures\":19}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":228,\"outFeatures\":376}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":376,\"outFeatures\":376}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":376,\"outFeatures\":376}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":376,\"outFeatures\":376}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":376,\"outFeatures\":19}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 111-feature, 45-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2397\nComponents:\n - input (input) params={\"shape\":[1,111]}\n - fc1 (linear) params={\"inFeatures\":111,\"outFeatures\":84}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":84,\"outFeatures\":404}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":404,\"outFeatures\":45}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":84}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":404}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 140-feature user input and a 123-feature item input, each through its own 2-layer MLP tower ending at width 485, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2398\nComponents:\n - user_input (input) params={\"shape\":[1,140]}\n - item_input (input) params={\"shape\":[1,123]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,140]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,123]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":140,\"outFeatures\":485}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":485,\"outFeatures\":485}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":123,\"outFeatures\":485}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":485,\"outFeatures\":485}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":970,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (109-feature input, 32 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2399\nComponents:\n - input (input) params={\"shape\":[1,109]}\n - fc1 (linear) params={\"inFeatures\":109,\"outFeatures\":10}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":10,\"outFeatures\":10}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":10,\"outFeatures\":32}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":109,\"outFeatures\":1207}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1207,\"outFeatures\":1207}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1207,\"outFeatures\":32}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 407-feature input with 40 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2400\nComponents:\n - input (input) params={\"shape\":[1,407]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,407]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":407,\"outFeatures\":32}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":32,\"outFeatures\":425}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":425,\"outFeatures\":40}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 2040-dim input: encode down to a 199-dim bottleneck and decode back to 2040. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2401\nComponents:\n - input (input) params={\"shape\":[1,2040]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,2040]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":2040,\"outFeatures\":527}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":527,\"outFeatures\":199}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":199,\"outFeatures\":527}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":527,\"outFeatures\":2040}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x27x27 image with 80 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2402\nComponents:\n - input (input) params={\"shape\":[1,3,27,27]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,27,27]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":11,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":11,\"outChannels\":8,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":8,\"outChannels\":53,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":53,\"outFeatures\":80}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 436-token sequences with 82 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2403\nComponents:\n - input (input) params={\"shape\":[1,436]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,436]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":34387,\"embeddingDim\":52}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":52,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":52,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":52,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":52,\"outFeatures\":82}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 423-token sequences with 53 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2404\nComponents:\n - input (input) params={\"shape\":[1,423]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,423]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":37005,\"embeddingDim\":200}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":200,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[200]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":200,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[200]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":200,\"outFeatures\":53}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 2926-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2406\nComponents:\n - input (input) params={\"shape\":[1,95]}\n - fc1 (linear) params={\"inFeatures\":95,\"outFeatures\":2926}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2926,\"outFeatures\":2926}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2926,\"outFeatures\":2926}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":2926,\"outFeatures\":12}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":95,\"outFeatures\":175}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":175,\"outFeatures\":175}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":175,\"outFeatures\":175}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":175,\"outFeatures\":12}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 171-feature, 27-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2407\nComponents:\n - input (input) params={\"shape\":[1,171]}\n - fc1 (linear) params={\"inFeatures\":171,\"outFeatures\":132}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":132,\"outFeatures\":223}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":223,\"outFeatures\":43}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":43,\"outFeatures\":342}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":342,\"outFeatures\":145}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":145,\"outFeatures\":27}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":132}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":223}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":43}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":342}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":145}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 73-feature user input and a 103-feature item input, each through its own 2-layer MLP tower ending at width 129, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2408\nComponents:\n - user_input (input) params={\"shape\":[1,73]}\n - item_input (input) params={\"shape\":[1,103]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,73]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,103]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":73,\"outFeatures\":129}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":129,\"outFeatures\":129}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":103,\"outFeatures\":129}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":129,\"outFeatures\":129}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":258,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (57-feature input, 38 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2409\nComponents:\n - input (input) params={\"shape\":[1,57]}\n - fc1 (linear) params={\"inFeatures\":57,\"outFeatures\":19}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":19,\"outFeatures\":19}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":19,\"outFeatures\":38}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":57,\"outFeatures\":1390}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1390,\"outFeatures\":1390}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1390,\"outFeatures\":38}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 360-feature input with 28 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2410\nComponents:\n - input (input) params={\"shape\":[1,360]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,360]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":360,\"outFeatures\":924}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":924,\"outFeatures\":242}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":242,\"outFeatures\":582}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":582,\"outFeatures\":744}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":744,\"outFeatures\":28}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 403-dim input: encode down to a 79-dim bottleneck and decode back to 403. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2411\nComponents:\n - input (input) params={\"shape\":[1,403]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,403]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":403,\"outFeatures\":997}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":997,\"outFeatures\":79}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":79,\"outFeatures\":997}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":997,\"outFeatures\":403}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x50x50 image with 29 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2412\nComponents:\n - input (input) params={\"shape\":[1,3,50,50]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,50,50]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":63,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":63,\"outChannels\":40,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":40,\"outChannels\":19,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":19,\"outChannels\":29,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":29,\"outFeatures\":29}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 392-token sequences with 72 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2413\nComponents:\n - input (input) params={\"shape\":[1,392]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,392]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":14645,\"embeddingDim\":50}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":50,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":50,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":50,\"outFeatures\":72}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 208-token sequences with 77 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2414\nComponents:\n - input (input) params={\"shape\":[1,208]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,208]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":36365,\"embeddingDim\":528}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":528,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[528]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":528,\"outFeatures\":77}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 1541-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2416\nComponents:\n - input (input) params={\"shape\":[1,82]}\n - fc1 (linear) params={\"inFeatures\":82,\"outFeatures\":1541}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":1541,\"outFeatures\":1541}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":1541,\"outFeatures\":1541}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":1541,\"outFeatures\":1541}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":1541,\"outFeatures\":9}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":82,\"outFeatures\":277}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":277,\"outFeatures\":277}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":277,\"outFeatures\":277}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":277,\"outFeatures\":277}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":277,\"outFeatures\":9}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 220-feature, 45-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2417\nComponents:\n - input (input) params={\"shape\":[1,220]}\n - fc1 (linear) params={\"inFeatures\":220,\"outFeatures\":253}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":253,\"outFeatures\":97}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":97,\"outFeatures\":223}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":223,\"outFeatures\":285}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":285,\"outFeatures\":238}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":238,\"outFeatures\":45}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":253}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":97}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":223}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":285}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":238}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 36-feature user input and a 45-feature item input, each through its own 2-layer MLP tower ending at width 117, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2418\nComponents:\n - user_input (input) params={\"shape\":[1,36]}\n - item_input (input) params={\"shape\":[1,45]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,36]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,45]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":36,\"outFeatures\":117}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":117,\"outFeatures\":117}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":45,\"outFeatures\":117}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":117,\"outFeatures\":117}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":234,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (126-feature input, 27 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2419\nComponents:\n - input (input) params={\"shape\":[1,126]}\n - fc1 (linear) params={\"inFeatures\":126,\"outFeatures\":23}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":23,\"outFeatures\":23}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":23,\"outFeatures\":27}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":126,\"outFeatures\":1066}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1066,\"outFeatures\":1066}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1066,\"outFeatures\":27}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 435-feature input with 156 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2420\nComponents:\n - input (input) params={\"shape\":[1,435]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,435]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":435,\"outFeatures\":207}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":207,\"outFeatures\":696}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":696,\"outFeatures\":368}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":368,\"outFeatures\":97}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":97,\"outFeatures\":1012}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":1012,\"outFeatures\":156}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 376-dim input: encode down to a 35-dim bottleneck and decode back to 376. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2421\nComponents:\n - input (input) params={\"shape\":[1,376]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,376]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":376,\"outFeatures\":161}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":161,\"outFeatures\":35}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":35,\"outFeatures\":161}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":161,\"outFeatures\":376}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x55x55 image with 37 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2422\nComponents:\n - input (input) params={\"shape\":[1,3,55,55]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,55,55]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":50,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":50,\"outChannels\":63,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":63,\"outChannels\":53,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":53,\"outChannels\":54,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":54,\"outFeatures\":37}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 484-token sequences with 71 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2423\nComponents:\n - input (input) params={\"shape\":[1,484]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,484]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":32030,\"embeddingDim\":488}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":488,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":488,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":488,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":488,\"outFeatures\":71}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 128-token sequences with 46 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2424\nComponents:\n - input (input) params={\"shape\":[1,128]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,128]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":37000,\"embeddingDim\":184}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":184,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[184]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":184,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[184]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":184,\"outFeatures\":46}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (204) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-2425\nComponents:\n - input (input) params={\"shape\":[1,243]}\n - embed (embedding) params={\"numEmbeddings\":33873,\"embeddingDim\":204}\n - attn (multiHeadAttention) params={\"embedDim\":204,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":204,\"outFeatures\":70}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":4}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3106-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2426\nComponents:\n - input (input) params={\"shape\":[1,60]}\n - fc1 (linear) params={\"inFeatures\":60,\"outFeatures\":3106}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3106,\"outFeatures\":3106}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3106,\"outFeatures\":3106}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3106,\"outFeatures\":3106}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3106,\"outFeatures\":4}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":60,\"outFeatures\":368}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":368,\"outFeatures\":368}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":368,\"outFeatures\":368}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":368,\"outFeatures\":368}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":368,\"outFeatures\":4}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 220-feature, 82-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2427\nComponents:\n - input (input) params={\"shape\":[1,220]}\n - fc1 (linear) params={\"inFeatures\":220,\"outFeatures\":326}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":326,\"outFeatures\":466}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":466,\"outFeatures\":339}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":339,\"outFeatures\":82}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":326}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":466}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":339}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 244-feature user input and a 224-feature item input, each through its own 2-layer MLP tower ending at width 256, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2428\nComponents:\n - user_input (input) params={\"shape\":[1,244]}\n - item_input (input) params={\"shape\":[1,224]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,244]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,224]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":244,\"outFeatures\":256}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":256,\"outFeatures\":256}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":224,\"outFeatures\":256}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":256,\"outFeatures\":256}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":512,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (78-feature input, 13 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2429\nComponents:\n - input (input) params={\"shape\":[1,78]}\n - fc1 (linear) params={\"inFeatures\":78,\"outFeatures\":16}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":16,\"outFeatures\":16}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":16,\"outFeatures\":13}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":78,\"outFeatures\":911}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":911,\"outFeatures\":911}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":911,\"outFeatures\":13}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 240-feature input with 5 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2430\nComponents:\n - input (input) params={\"shape\":[1,240]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,240]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":240,\"outFeatures\":925}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":925,\"outFeatures\":236}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":236,\"outFeatures\":401}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":401,\"outFeatures\":713}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":713,\"outFeatures\":896}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":896,\"outFeatures\":866}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":866,\"outFeatures\":5}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1156-dim input: encode down to a 182-dim bottleneck and decode back to 1156. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2431\nComponents:\n - input (input) params={\"shape\":[1,1156]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1156]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1156,\"outFeatures\":449}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":449,\"outFeatures\":182}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":182,\"outFeatures\":449}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":449,\"outFeatures\":1156}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x61x61 image with 10 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2432\nComponents:\n - input (input) params={\"shape\":[1,3,61,61]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,61,61]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":22,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":22,\"outChannels\":48,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":48,\"outFeatures\":10}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 141-token sequences with 91 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2433\nComponents:\n - input (input) params={\"shape\":[1,141]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,141]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":15454,\"embeddingDim\":62}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":62,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":62,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":62,\"outFeatures\":91}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 433-token sequences with 3 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2434\nComponents:\n - input (input) params={\"shape\":[1,433]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,433]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":45139,\"embeddingDim\":128}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":128,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[128]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":128,\"outFeatures\":3}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (322) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-2435\nComponents:\n - input (input) params={\"shape\":[1,199]}\n - embed (embedding) params={\"numEmbeddings\":37060,\"embeddingDim\":322}\n - attn (multiHeadAttention) params={\"embedDim\":322,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":322,\"outFeatures\":66}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 1680-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2436\nComponents:\n - input (input) params={\"shape\":[1,109]}\n - fc1 (linear) params={\"inFeatures\":109,\"outFeatures\":1680}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":1680,\"outFeatures\":1680}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":1680,\"outFeatures\":30}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":109,\"outFeatures\":286}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":286,\"outFeatures\":286}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":286,\"outFeatures\":30}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 94-feature, 50-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2437\nComponents:\n - input (input) params={\"shape\":[1,94]}\n - fc1 (linear) params={\"inFeatures\":94,\"outFeatures\":204}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":204,\"outFeatures\":506}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":506,\"outFeatures\":69}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":69,\"outFeatures\":294}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":294,\"outFeatures\":50}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":204}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":506}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":69}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":294}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 35-feature user input and a 223-feature item input, each through its own 2-layer MLP tower ending at width 203, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2438\nComponents:\n - user_input (input) params={\"shape\":[1,35]}\n - item_input (input) params={\"shape\":[1,223]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,35]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,223]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":35,\"outFeatures\":203}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":203,\"outFeatures\":203}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":223,\"outFeatures\":203}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":203,\"outFeatures\":203}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":406,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (68-feature input, 12 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2439\nComponents:\n - input (input) params={\"shape\":[1,68]}\n - fc1 (linear) params={\"inFeatures\":68,\"outFeatures\":18}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":18,\"outFeatures\":18}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":18,\"outFeatures\":12}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":68,\"outFeatures\":1348}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1348,\"outFeatures\":1348}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1348,\"outFeatures\":12}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 377-feature input with 19 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2440\nComponents:\n - input (input) params={\"shape\":[1,377]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,377]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":377,\"outFeatures\":605}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":605,\"outFeatures\":221}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":221,\"outFeatures\":19}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1799-dim input: encode down to a 67-dim bottleneck and decode back to 1799. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2441\nComponents:\n - input (input) params={\"shape\":[1,1799]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1799]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1799,\"outFeatures\":730}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":730,\"outFeatures\":67}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":67,\"outFeatures\":730}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":730,\"outFeatures\":1799}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x24x24 image with 51 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2442\nComponents:\n - input (input) params={\"shape\":[1,3,24,24]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,24,24]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":9,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":9,\"outChannels\":35,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":35,\"outChannels\":40,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":40,\"outChannels\":59,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":59,\"outFeatures\":51}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 512-token sequences with 25 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2443\nComponents:\n - input (input) params={\"shape\":[1,512]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,512]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":15097,\"embeddingDim\":80}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":80,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":80,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":80,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":80,\"outFeatures\":25}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 377-token sequences with 17 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2444\nComponents:\n - input (input) params={\"shape\":[1,377]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,377]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":48546,\"embeddingDim\":720}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":720,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[720]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":720,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[720]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":720,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[720]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":720,\"outFeatures\":17}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (74) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-2445\nComponents:\n - input (input) params={\"shape\":[1,337]}\n - embed (embedding) params={\"numEmbeddings\":28682,\"embeddingDim\":74}\n - attn (multiHeadAttention) params={\"embedDim\":74,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":74,\"outFeatures\":29}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 2792-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2446\nComponents:\n - input (input) params={\"shape\":[1,160]}\n - fc1 (linear) params={\"inFeatures\":160,\"outFeatures\":2792}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2792,\"outFeatures\":2792}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2792,\"outFeatures\":2792}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":2792,\"outFeatures\":2792}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":2792,\"outFeatures\":20}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":160,\"outFeatures\":265}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":265,\"outFeatures\":265}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":265,\"outFeatures\":265}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":265,\"outFeatures\":265}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":265,\"outFeatures\":20}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 20-feature, 37-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2447\nComponents:\n - input (input) params={\"shape\":[1,20]}\n - fc1 (linear) params={\"inFeatures\":20,\"outFeatures\":337}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":337,\"outFeatures\":473}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":473,\"outFeatures\":510}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":510,\"outFeatures\":37}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":337}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":473}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":510}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 195-feature user input and a 85-feature item input, each through its own 2-layer MLP tower ending at width 281, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2448\nComponents:\n - user_input (input) params={\"shape\":[1,195]}\n - item_input (input) params={\"shape\":[1,85]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,195]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,85]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":195,\"outFeatures\":281}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":281,\"outFeatures\":281}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":85,\"outFeatures\":281}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":281,\"outFeatures\":281}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":562,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (47-feature input, 37 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2449\nComponents:\n - input (input) params={\"shape\":[1,47]}\n - fc1 (linear) params={\"inFeatures\":47,\"outFeatures\":5}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":5,\"outFeatures\":5}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":5,\"outFeatures\":37}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":47,\"outFeatures\":779}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":779,\"outFeatures\":779}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":779,\"outFeatures\":37}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 207-feature input with 161 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2450\nComponents:\n - input (input) params={\"shape\":[1,207]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,207]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":207,\"outFeatures\":362}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":362,\"outFeatures\":155}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":155,\"outFeatures\":110}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":110,\"outFeatures\":212}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":212,\"outFeatures\":324}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":324,\"outFeatures\":138}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":138,\"outFeatures\":161}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 2044-dim input: encode down to a 108-dim bottleneck and decode back to 2044. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2451\nComponents:\n - input (input) params={\"shape\":[1,2044]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,2044]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":2044,\"outFeatures\":362}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":362,\"outFeatures\":108}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":108,\"outFeatures\":362}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":362,\"outFeatures\":2044}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x34x34 image with 33 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2452\nComponents:\n - input (input) params={\"shape\":[1,3,34,34]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,34,34]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":33,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":33,\"outChannels\":28,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":28,\"outFeatures\":33}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 392-token sequences with 99 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2453\nComponents:\n - input (input) params={\"shape\":[1,392]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,392]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":9406,\"embeddingDim\":100}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":100,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":100,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":100,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":100,\"outFeatures\":99}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 437-token sequences with 25 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2454\nComponents:\n - input (input) params={\"shape\":[1,437]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,437]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":36648,\"embeddingDim\":140}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":140,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[140]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":140,\"outFeatures\":25}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 2112-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2456\nComponents:\n - input (input) params={\"shape\":[1,88]}\n - fc1 (linear) params={\"inFeatures\":88,\"outFeatures\":2112}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2112,\"outFeatures\":2112}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2112,\"outFeatures\":2112}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":2112,\"outFeatures\":27}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":88,\"outFeatures\":290}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":290,\"outFeatures\":290}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":290,\"outFeatures\":290}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":290,\"outFeatures\":27}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 65-feature, 74-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2457\nComponents:\n - input (input) params={\"shape\":[1,65]}\n - fc1 (linear) params={\"inFeatures\":65,\"outFeatures\":413}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":413,\"outFeatures\":212}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":212,\"outFeatures\":375}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":375,\"outFeatures\":74}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":413}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":212}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":375}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 188-feature user input and a 195-feature item input, each through its own 2-layer MLP tower ending at width 92, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2458\nComponents:\n - user_input (input) params={\"shape\":[1,188]}\n - item_input (input) params={\"shape\":[1,195]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,188]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,195]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":188,\"outFeatures\":92}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":92,\"outFeatures\":92}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":195,\"outFeatures\":92}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":92,\"outFeatures\":92}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":184,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (88-feature input, 4 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2459\nComponents:\n - input (input) params={\"shape\":[1,88]}\n - fc1 (linear) params={\"inFeatures\":88,\"outFeatures\":6}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":6,\"outFeatures\":6}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":6,\"outFeatures\":4}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":88,\"outFeatures\":1175}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1175,\"outFeatures\":1175}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1175,\"outFeatures\":4}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 128-feature input with 131 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2460\nComponents:\n - input (input) params={\"shape\":[1,128]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,128]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":128,\"outFeatures\":972}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":972,\"outFeatures\":600}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":600,\"outFeatures\":126}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":126,\"outFeatures\":991}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":991,\"outFeatures\":131}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 737-dim input: encode down to a 108-dim bottleneck and decode back to 737. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2461\nComponents:\n - input (input) params={\"shape\":[1,737]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,737]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":737,\"outFeatures\":540}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":540,\"outFeatures\":108}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":108,\"outFeatures\":540}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":540,\"outFeatures\":737}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x45x45 image with 33 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2462\nComponents:\n - input (input) params={\"shape\":[1,3,45,45]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,45,45]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":18,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":18,\"outChannels\":12,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":12,\"outFeatures\":33}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 342-token sequences with 38 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2463\nComponents:\n - input (input) params={\"shape\":[1,342]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,342]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":15209,\"embeddingDim\":368}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":368,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":368,\"outFeatures\":38}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 215-token sequences with 10 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2464\nComponents:\n - input (input) params={\"shape\":[1,215]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,215]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":12049,\"embeddingDim\":176}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":176,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[176]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":176,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[176]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":176,\"outFeatures\":10}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (360) is not divisible by numHeads (7). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-2465\nComponents:\n - input (input) params={\"shape\":[1,405]}\n - embed (embedding) params={\"numEmbeddings\":8772,\"embeddingDim\":360}\n - attn (multiHeadAttention) params={\"embedDim\":360,\"numHeads\":7}\n - head (linear) params={\"inFeatures\":360,\"outFeatures\":17}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":8}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3750-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2466\nComponents:\n - input (input) params={\"shape\":[1,250]}\n - fc1 (linear) params={\"inFeatures\":250,\"outFeatures\":3750}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3750,\"outFeatures\":3750}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3750,\"outFeatures\":3750}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3750,\"outFeatures\":3750}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3750,\"outFeatures\":42}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":250,\"outFeatures\":339}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":339,\"outFeatures\":339}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":339,\"outFeatures\":339}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":339,\"outFeatures\":339}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":339,\"outFeatures\":42}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 78-feature, 86-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2467\nComponents:\n - input (input) params={\"shape\":[1,78]}\n - fc1 (linear) params={\"inFeatures\":78,\"outFeatures\":196}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":196,\"outFeatures\":313}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":313,\"outFeatures\":417}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":417,\"outFeatures\":443}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":443,\"outFeatures\":86}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":196}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":313}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":417}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":443}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 99-feature user input and a 92-feature item input, each through its own 2-layer MLP tower ending at width 118, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2468\nComponents:\n - user_input (input) params={\"shape\":[1,99]}\n - item_input (input) params={\"shape\":[1,92]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,99]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,92]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":99,\"outFeatures\":118}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":118,\"outFeatures\":118}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":92,\"outFeatures\":118}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":118,\"outFeatures\":118}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":236,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (99-feature input, 29 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2469\nComponents:\n - input (input) params={\"shape\":[1,99]}\n - fc1 (linear) params={\"inFeatures\":99,\"outFeatures\":10}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":10,\"outFeatures\":10}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":10,\"outFeatures\":29}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":99,\"outFeatures\":1173}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1173,\"outFeatures\":1173}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1173,\"outFeatures\":29}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 60-feature input with 131 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2470\nComponents:\n - input (input) params={\"shape\":[1,60]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,60]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":60,\"outFeatures\":749}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":749,\"outFeatures\":284}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":284,\"outFeatures\":604}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":604,\"outFeatures\":16}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":16,\"outFeatures\":131}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1637-dim input: encode down to a 169-dim bottleneck and decode back to 1637. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2471\nComponents:\n - input (input) params={\"shape\":[1,1637]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1637]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1637,\"outFeatures\":668}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":668,\"outFeatures\":169}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":169,\"outFeatures\":668}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":668,\"outFeatures\":1637}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x60x60 image with 40 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2472\nComponents:\n - input (input) params={\"shape\":[1,3,60,60]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,60,60]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":13,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":13,\"outChannels\":21,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":21,\"outChannels\":17,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":17,\"outChannels\":38,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":38,\"outFeatures\":40}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 317-token sequences with 69 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2473\nComponents:\n - input (input) params={\"shape\":[1,317]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,317]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":10985,\"embeddingDim\":20}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":20,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":20,\"outFeatures\":69}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 278-token sequences with 67 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2474\nComponents:\n - input (input) params={\"shape\":[1,278]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,278]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":19948,\"embeddingDim\":128}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":128,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[128]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":128,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[128]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":128,\"outFeatures\":67}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 2371-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2476\nComponents:\n - input (input) params={\"shape\":[1,164]}\n - fc1 (linear) params={\"inFeatures\":164,\"outFeatures\":2371}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2371,\"outFeatures\":2371}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":2371,\"outFeatures\":19}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":164,\"outFeatures\":92}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":92,\"outFeatures\":92}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":92,\"outFeatures\":19}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 149-feature, 67-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2477\nComponents:\n - input (input) params={\"shape\":[1,149]}\n - fc1 (linear) params={\"inFeatures\":149,\"outFeatures\":305}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":305,\"outFeatures\":111}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":111,\"outFeatures\":427}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":427,\"outFeatures\":394}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":394,\"outFeatures\":420}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":420,\"outFeatures\":67}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":305}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":111}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":427}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":394}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":420}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 189-feature user input and a 113-feature item input, each through its own 2-layer MLP tower ending at width 139, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2478\nComponents:\n - user_input (input) params={\"shape\":[1,189]}\n - item_input (input) params={\"shape\":[1,113]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,189]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,113]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":189,\"outFeatures\":139}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":139,\"outFeatures\":139}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":113,\"outFeatures\":139}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":139,\"outFeatures\":139}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":278,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (38-feature input, 2 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2479\nComponents:\n - input (input) params={\"shape\":[1,38]}\n - fc1 (linear) params={\"inFeatures\":38,\"outFeatures\":19}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":19,\"outFeatures\":19}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":19,\"outFeatures\":2}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":38,\"outFeatures\":1059}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1059,\"outFeatures\":1059}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1059,\"outFeatures\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 510-feature input with 91 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2480\nComponents:\n - input (input) params={\"shape\":[1,510]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,510]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":510,\"outFeatures\":213}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":213,\"outFeatures\":1004}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":1004,\"outFeatures\":494}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":494,\"outFeatures\":846}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":846,\"outFeatures\":777}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":777,\"outFeatures\":91}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 912-dim input: encode down to a 157-dim bottleneck and decode back to 912. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2481\nComponents:\n - input (input) params={\"shape\":[1,912]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,912]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":912,\"outFeatures\":126}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":126,\"outFeatures\":157}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":157,\"outFeatures\":126}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":126,\"outFeatures\":912}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x51x51 image with 12 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2482\nComponents:\n - input (input) params={\"shape\":[1,3,51,51]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,51,51]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":46,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":46,\"outChannels\":16,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":16,\"outChannels\":35,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":35,\"outFeatures\":12}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 280-token sequences with 62 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2483\nComponents:\n - input (input) params={\"shape\":[1,280]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,280]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":49257,\"embeddingDim\":512}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":512,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":512,\"outFeatures\":62}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 209-token sequences with 66 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2484\nComponents:\n - input (input) params={\"shape\":[1,209]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,209]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":39082,\"embeddingDim\":360}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":360,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[360]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":360,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[360]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":360,\"outFeatures\":66}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 3679-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2486\nComponents:\n - input (input) params={\"shape\":[1,151]}\n - fc1 (linear) params={\"inFeatures\":151,\"outFeatures\":3679}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3679,\"outFeatures\":3679}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3679,\"outFeatures\":3679}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":3679,\"outFeatures\":32}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":151,\"outFeatures\":236}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":236,\"outFeatures\":236}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":236,\"outFeatures\":236}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":236,\"outFeatures\":32}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 164-feature, 21-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2487\nComponents:\n - input (input) params={\"shape\":[1,164]}\n - fc1 (linear) params={\"inFeatures\":164,\"outFeatures\":163}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":163,\"outFeatures\":122}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":122,\"outFeatures\":450}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":450,\"outFeatures\":132}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":132,\"outFeatures\":119}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":119,\"outFeatures\":21}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":163}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":122}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":450}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":132}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":119}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 162-feature user input and a 167-feature item input, each through its own 2-layer MLP tower ending at width 65, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2488\nComponents:\n - user_input (input) params={\"shape\":[1,162]}\n - item_input (input) params={\"shape\":[1,167]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,162]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,167]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":162,\"outFeatures\":65}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":65,\"outFeatures\":65}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":167,\"outFeatures\":65}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":65,\"outFeatures\":65}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":130,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (60-feature input, 24 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2489\nComponents:\n - input (input) params={\"shape\":[1,60]}\n - fc1 (linear) params={\"inFeatures\":60,\"outFeatures\":4}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":4,\"outFeatures\":4}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":4,\"outFeatures\":24}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":60,\"outFeatures\":686}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":686,\"outFeatures\":686}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":686,\"outFeatures\":24}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 32-feature input with 192 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2490\nComponents:\n - input (input) params={\"shape\":[1,32]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,32]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":32,\"outFeatures\":954}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":954,\"outFeatures\":645}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":645,\"outFeatures\":670}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":670,\"outFeatures\":841}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":841,\"outFeatures\":192}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1924-dim input: encode down to a 69-dim bottleneck and decode back to 1924. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2491\nComponents:\n - input (input) params={\"shape\":[1,1924]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1924]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1924,\"outFeatures\":301}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":301,\"outFeatures\":69}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":69,\"outFeatures\":301}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":301,\"outFeatures\":1924}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x32x32 image with 28 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2492\nComponents:\n - input (input) params={\"shape\":[1,3,32,32]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,32,32]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":24,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":24,\"outChannels\":39,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":39,\"outFeatures\":28}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 75-token sequences with 87 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2493\nComponents:\n - input (input) params={\"shape\":[1,75]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,75]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":18120,\"embeddingDim\":114}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":114,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":114,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":114,\"outFeatures\":87}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 439-token sequences with 8 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2494\nComponents:\n - input (input) params={\"shape\":[1,439]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,439]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":10122,\"embeddingDim\":304}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":304,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[304]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":304,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[304]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":304,\"outFeatures\":8}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (378) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-2495\nComponents:\n - input (input) params={\"shape\":[1,242]}\n - embed (embedding) params={\"numEmbeddings\":42488,\"embeddingDim\":378}\n - attn (multiHeadAttention) params={\"embedDim\":378,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":378,\"outFeatures\":100}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3314-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2496\nComponents:\n - input (input) params={\"shape\":[1,81]}\n - fc1 (linear) params={\"inFeatures\":81,\"outFeatures\":3314}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3314,\"outFeatures\":3314}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3314,\"outFeatures\":3314}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3314,\"outFeatures\":3314}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3314,\"outFeatures\":45}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":81,\"outFeatures\":275}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":275,\"outFeatures\":275}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":275,\"outFeatures\":275}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":275,\"outFeatures\":275}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":275,\"outFeatures\":45}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 190-feature, 4-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2497\nComponents:\n - input (input) params={\"shape\":[1,190]}\n - fc1 (linear) params={\"inFeatures\":190,\"outFeatures\":410}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":410,\"outFeatures\":304}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":304,\"outFeatures\":62}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":62,\"outFeatures\":425}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":425,\"outFeatures\":236}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":236,\"outFeatures\":4}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":410}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":304}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":62}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":425}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":236}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 71-feature user input and a 188-feature item input, each through its own 2-layer MLP tower ending at width 509, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2498\nComponents:\n - user_input (input) params={\"shape\":[1,71]}\n - item_input (input) params={\"shape\":[1,188]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,71]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,188]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":71,\"outFeatures\":509}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":509,\"outFeatures\":509}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":188,\"outFeatures\":509}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":509,\"outFeatures\":509}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":1018,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (52-feature input, 21 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2499\nComponents:\n - input (input) params={\"shape\":[1,52]}\n - fc1 (linear) params={\"inFeatures\":52,\"outFeatures\":20}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":20,\"outFeatures\":20}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":20,\"outFeatures\":21}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":52,\"outFeatures\":1361}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1361,\"outFeatures\":1361}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1361,\"outFeatures\":21}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 458-feature input with 157 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2500\nComponents:\n - input (input) params={\"shape\":[1,458]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,458]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":458,\"outFeatures\":197}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":197,\"outFeatures\":763}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":763,\"outFeatures\":157}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1550-dim input: encode down to a 130-dim bottleneck and decode back to 1550. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2501\nComponents:\n - input (input) params={\"shape\":[1,1550]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1550]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1550,\"outFeatures\":664}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":664,\"outFeatures\":130}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":130,\"outFeatures\":664}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":664,\"outFeatures\":1550}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x43x43 image with 2 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2502\nComponents:\n - input (input) params={\"shape\":[1,3,43,43]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,43,43]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":11,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":11,\"outChannels\":54,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":54,\"outChannels\":39,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":39,\"outFeatures\":2}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 56-token sequences with 32 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2503\nComponents:\n - input (input) params={\"shape\":[1,56]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,56]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":46706,\"embeddingDim\":70}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":70,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":70,\"outFeatures\":32}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 347-token sequences with 85 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2504\nComponents:\n - input (input) params={\"shape\":[1,347]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,347]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":12634,\"embeddingDim\":576}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":576,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[576]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":576,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[576]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":576,\"outFeatures\":85}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (90) is not divisible by numHeads (7). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-2505\nComponents:\n - input (input) params={\"shape\":[1,366]}\n - embed (embedding) params={\"numEmbeddings\":31212,\"embeddingDim\":90}\n - attn (multiHeadAttention) params={\"embedDim\":90,\"numHeads\":7}\n - head (linear) params={\"inFeatures\":90,\"outFeatures\":12}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3862-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2506\nComponents:\n - input (input) params={\"shape\":[1,200]}\n - fc1 (linear) params={\"inFeatures\":200,\"outFeatures\":3862}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3862,\"outFeatures\":3862}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3862,\"outFeatures\":3862}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3862,\"outFeatures\":3862}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3862,\"outFeatures\":38}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":200,\"outFeatures\":68}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":68,\"outFeatures\":68}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":68,\"outFeatures\":68}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":68,\"outFeatures\":68}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":68,\"outFeatures\":38}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 141-feature, 5-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2507\nComponents:\n - input (input) params={\"shape\":[1,141]}\n - fc1 (linear) params={\"inFeatures\":141,\"outFeatures\":219}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":219,\"outFeatures\":115}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":115,\"outFeatures\":431}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":431,\"outFeatures\":5}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":219}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":115}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":431}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 164-feature user input and a 58-feature item input, each through its own 2-layer MLP tower ending at width 188, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2508\nComponents:\n - user_input (input) params={\"shape\":[1,164]}\n - item_input (input) params={\"shape\":[1,58]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,164]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,58]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":164,\"outFeatures\":188}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":188,\"outFeatures\":188}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":58,\"outFeatures\":188}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":188,\"outFeatures\":188}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":376,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (35-feature input, 48 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2509\nComponents:\n - input (input) params={\"shape\":[1,35]}\n - fc1 (linear) params={\"inFeatures\":35,\"outFeatures\":21}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":21,\"outFeatures\":21}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":21,\"outFeatures\":48}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":35,\"outFeatures\":842}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":842,\"outFeatures\":842}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":842,\"outFeatures\":48}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 201-feature input with 70 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2510\nComponents:\n - input (input) params={\"shape\":[1,201]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,201]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":201,\"outFeatures\":818}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":818,\"outFeatures\":720}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":720,\"outFeatures\":128}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":128,\"outFeatures\":489}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":489,\"outFeatures\":70}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1426-dim input: encode down to a 53-dim bottleneck and decode back to 1426. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2511\nComponents:\n - input (input) params={\"shape\":[1,1426]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1426]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1426,\"outFeatures\":469}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":469,\"outFeatures\":53}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":53,\"outFeatures\":469}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":469,\"outFeatures\":1426}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x49x49 image with 52 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2512\nComponents:\n - input (input) params={\"shape\":[1,3,49,49]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,49,49]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":38,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":38,\"outChannels\":22,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":22,\"outChannels\":17,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":17,\"outFeatures\":52}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 266-token sequences with 80 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2513\nComponents:\n - input (input) params={\"shape\":[1,266]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,266]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":42980,\"embeddingDim\":48}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":48,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":48,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":48,\"outFeatures\":80}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 117-token sequences with 96 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2514\nComponents:\n - input (input) params={\"shape\":[1,117]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,117]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":32228,\"embeddingDim\":560}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":560,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[560]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":560,\"outFeatures\":96}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3121-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2516\nComponents:\n - input (input) params={\"shape\":[1,66]}\n - fc1 (linear) params={\"inFeatures\":66,\"outFeatures\":3121}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3121,\"outFeatures\":3121}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3121,\"outFeatures\":3121}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3121,\"outFeatures\":3121}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3121,\"outFeatures\":23}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":66,\"outFeatures\":353}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":353,\"outFeatures\":353}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":353,\"outFeatures\":353}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":353,\"outFeatures\":353}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":353,\"outFeatures\":23}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 177-feature, 81-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2517\nComponents:\n - input (input) params={\"shape\":[1,177]}\n - fc1 (linear) params={\"inFeatures\":177,\"outFeatures\":162}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":162,\"outFeatures\":249}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":249,\"outFeatures\":54}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":54,\"outFeatures\":120}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":120,\"outFeatures\":81}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":162}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":249}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":54}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":120}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 231-feature user input and a 134-feature item input, each through its own 2-layer MLP tower ending at width 179, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2518\nComponents:\n - user_input (input) params={\"shape\":[1,231]}\n - item_input (input) params={\"shape\":[1,134]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,231]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,134]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":231,\"outFeatures\":179}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":179,\"outFeatures\":179}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":134,\"outFeatures\":179}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":179,\"outFeatures\":179}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":358,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (97-feature input, 32 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2519\nComponents:\n - input (input) params={\"shape\":[1,97]}\n - fc1 (linear) params={\"inFeatures\":97,\"outFeatures\":14}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":14,\"outFeatures\":14}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":14,\"outFeatures\":32}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":97,\"outFeatures\":746}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":746,\"outFeatures\":746}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":746,\"outFeatures\":32}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 389-feature input with 41 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2520\nComponents:\n - input (input) params={\"shape\":[1,389]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,389]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":389,\"outFeatures\":619}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":619,\"outFeatures\":911}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":911,\"outFeatures\":909}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":909,\"outFeatures\":97}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":97,\"outFeatures\":41}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 256-dim input: encode down to a 28-dim bottleneck and decode back to 256. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2521\nComponents:\n - input (input) params={\"shape\":[1,256]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,256]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":256,\"outFeatures\":565}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":565,\"outFeatures\":28}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":28,\"outFeatures\":565}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":565,\"outFeatures\":256}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x42x42 image with 12 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2522\nComponents:\n - input (input) params={\"shape\":[1,3,42,42]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,42,42]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":20,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":20,\"outChannels\":64,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":64,\"outChannels\":54,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":54,\"outChannels\":52,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":52,\"outFeatures\":12}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 41-token sequences with 49 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2523\nComponents:\n - input (input) params={\"shape\":[1,41]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,41]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":15659,\"embeddingDim\":64}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":64,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":64,\"outFeatures\":49}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 452-token sequences with 35 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2524\nComponents:\n - input (input) params={\"shape\":[1,452]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,452]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":45740,\"embeddingDim\":88}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":88,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[88]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":88,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[88]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":88,\"outFeatures\":35}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 3804-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2526\nComponents:\n - input (input) params={\"shape\":[1,145]}\n - fc1 (linear) params={\"inFeatures\":145,\"outFeatures\":3804}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3804,\"outFeatures\":3804}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3804,\"outFeatures\":3804}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":3804,\"outFeatures\":49}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":145,\"outFeatures\":70}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":70,\"outFeatures\":70}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":70,\"outFeatures\":70}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":70,\"outFeatures\":49}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 202-feature, 90-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2527\nComponents:\n - input (input) params={\"shape\":[1,202]}\n - fc1 (linear) params={\"inFeatures\":202,\"outFeatures\":436}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":436,\"outFeatures\":169}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":169,\"outFeatures\":90}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":436}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":169}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 126-feature user input and a 72-feature item input, each through its own 2-layer MLP tower ending at width 409, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2528\nComponents:\n - user_input (input) params={\"shape\":[1,126]}\n - item_input (input) params={\"shape\":[1,72]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,126]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,72]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":126,\"outFeatures\":409}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":409,\"outFeatures\":409}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":72,\"outFeatures\":409}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":409,\"outFeatures\":409}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":818,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (105-feature input, 38 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2529\nComponents:\n - input (input) params={\"shape\":[1,105]}\n - fc1 (linear) params={\"inFeatures\":105,\"outFeatures\":15}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":15,\"outFeatures\":15}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":15,\"outFeatures\":38}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":105,\"outFeatures\":866}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":866,\"outFeatures\":866}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":866,\"outFeatures\":38}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 322-feature input with 182 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2530\nComponents:\n - input (input) params={\"shape\":[1,322]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,322]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":322,\"outFeatures\":212}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":212,\"outFeatures\":915}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":915,\"outFeatures\":182}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 668-dim input: encode down to a 70-dim bottleneck and decode back to 668. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2531\nComponents:\n - input (input) params={\"shape\":[1,668]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,668]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":668,\"outFeatures\":347}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":347,\"outFeatures\":70}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":70,\"outFeatures\":347}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":347,\"outFeatures\":668}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x52x52 image with 38 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2532\nComponents:\n - input (input) params={\"shape\":[1,3,52,52]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,52,52]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":48,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":48,\"outChannels\":54,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":54,\"outChannels\":46,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":46,\"outFeatures\":38}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 459-token sequences with 38 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2533\nComponents:\n - input (input) params={\"shape\":[1,459]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,459]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":40898,\"embeddingDim\":216}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":216,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":216,\"outFeatures\":38}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 100-token sequences with 97 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2534\nComponents:\n - input (input) params={\"shape\":[1,100]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,100]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":17145,\"embeddingDim\":104}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":104,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[104]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":104,\"outFeatures\":97}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (394) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-2535\nComponents:\n - input (input) params={\"shape\":[1,232]}\n - embed (embedding) params={\"numEmbeddings\":20100,\"embeddingDim\":394}\n - attn (multiHeadAttention) params={\"embedDim\":394,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":394,\"outFeatures\":8}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 3305-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2536\nComponents:\n - input (input) params={\"shape\":[1,152]}\n - fc1 (linear) params={\"inFeatures\":152,\"outFeatures\":3305}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3305,\"outFeatures\":3305}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3305,\"outFeatures\":3305}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":3305,\"outFeatures\":28}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":152,\"outFeatures\":112}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":112,\"outFeatures\":112}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":112,\"outFeatures\":112}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":112,\"outFeatures\":28}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 97-feature, 38-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2537\nComponents:\n - input (input) params={\"shape\":[1,97]}\n - fc1 (linear) params={\"inFeatures\":97,\"outFeatures\":135}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":135,\"outFeatures\":372}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":372,\"outFeatures\":38}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":135}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":372}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 49-feature user input and a 156-feature item input, each through its own 2-layer MLP tower ending at width 433, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2538\nComponents:\n - user_input (input) params={\"shape\":[1,49]}\n - item_input (input) params={\"shape\":[1,156]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,49]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,156]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":49,\"outFeatures\":433}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":433,\"outFeatures\":433}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":156,\"outFeatures\":433}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":433,\"outFeatures\":433}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":866,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (46-feature input, 4 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2539\nComponents:\n - input (input) params={\"shape\":[1,46]}\n - fc1 (linear) params={\"inFeatures\":46,\"outFeatures\":9}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":9,\"outFeatures\":9}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":9,\"outFeatures\":4}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":46,\"outFeatures\":1319}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1319,\"outFeatures\":1319}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1319,\"outFeatures\":4}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 376-feature input with 24 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2540\nComponents:\n - input (input) params={\"shape\":[1,376]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,376]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":376,\"outFeatures\":795}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":795,\"outFeatures\":615}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":615,\"outFeatures\":80}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":80,\"outFeatures\":270}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":270,\"outFeatures\":1014}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":1014,\"outFeatures\":466}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":466,\"outFeatures\":24}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1168-dim input: encode down to a 145-dim bottleneck and decode back to 1168. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2541\nComponents:\n - input (input) params={\"shape\":[1,1168]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1168]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1168,\"outFeatures\":201}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":201,\"outFeatures\":145}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":145,\"outFeatures\":201}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":201,\"outFeatures\":1168}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x39x39 image with 39 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2542\nComponents:\n - input (input) params={\"shape\":[1,3,39,39]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,39,39]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":16,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":16,\"outChannels\":8,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":8,\"outFeatures\":39}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 47-token sequences with 65 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2543\nComponents:\n - input (input) params={\"shape\":[1,47]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,47]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":33553,\"embeddingDim\":22}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":22,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":22,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":22,\"outFeatures\":65}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 501-token sequences with 76 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2544\nComponents:\n - input (input) params={\"shape\":[1,501]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,501]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":19272,\"embeddingDim\":304}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":304,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[304]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":304,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[304]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":304,\"outFeatures\":76}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (346) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-2545\nComponents:\n - input (input) params={\"shape\":[1,195]}\n - embed (embedding) params={\"numEmbeddings\":12602,\"embeddingDim\":346}\n - attn (multiHeadAttention) params={\"embedDim\":346,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":346,\"outFeatures\":26}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3746-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2546\nComponents:\n - input (input) params={\"shape\":[1,33]}\n - fc1 (linear) params={\"inFeatures\":33,\"outFeatures\":3746}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3746,\"outFeatures\":3746}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3746,\"outFeatures\":3746}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3746,\"outFeatures\":3746}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3746,\"outFeatures\":6}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":33,\"outFeatures\":64}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":64,\"outFeatures\":64}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":64,\"outFeatures\":64}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":64,\"outFeatures\":64}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":64,\"outFeatures\":6}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 16-feature, 33-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2547\nComponents:\n - input (input) params={\"shape\":[1,16]}\n - fc1 (linear) params={\"inFeatures\":16,\"outFeatures\":192}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":192,\"outFeatures\":233}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":233,\"outFeatures\":33}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":192}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":233}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 147-feature user input and a 203-feature item input, each through its own 2-layer MLP tower ending at width 458, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2548\nComponents:\n - user_input (input) params={\"shape\":[1,147]}\n - item_input (input) params={\"shape\":[1,203]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,147]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,203]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":147,\"outFeatures\":458}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":458,\"outFeatures\":458}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":203,\"outFeatures\":458}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":458,\"outFeatures\":458}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":916,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (102-feature input, 27 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2549\nComponents:\n - input (input) params={\"shape\":[1,102]}\n - fc1 (linear) params={\"inFeatures\":102,\"outFeatures\":18}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":18,\"outFeatures\":18}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":18,\"outFeatures\":27}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":102,\"outFeatures\":1188}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1188,\"outFeatures\":1188}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1188,\"outFeatures\":27}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 122-feature input with 69 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2550\nComponents:\n - input (input) params={\"shape\":[1,122]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,122]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":122,\"outFeatures\":361}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":361,\"outFeatures\":193}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":193,\"outFeatures\":499}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":499,\"outFeatures\":347}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":347,\"outFeatures\":444}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":444,\"outFeatures\":69}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1075-dim input: encode down to a 124-dim bottleneck and decode back to 1075. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2551\nComponents:\n - input (input) params={\"shape\":[1,1075]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1075]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1075,\"outFeatures\":804}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":804,\"outFeatures\":124}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":124,\"outFeatures\":804}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":804,\"outFeatures\":1075}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x29x29 image with 29 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2552\nComponents:\n - input (input) params={\"shape\":[1,3,29,29]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,29,29]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":60,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":60,\"outChannels\":54,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":54,\"outChannels\":21,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":21,\"outFeatures\":29}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 170-token sequences with 6 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2553\nComponents:\n - input (input) params={\"shape\":[1,170]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,170]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":34518,\"embeddingDim\":28}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":28,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":28,\"outFeatures\":6}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 344-token sequences with 41 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2554\nComponents:\n - input (input) params={\"shape\":[1,344]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,344]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":33175,\"embeddingDim\":168}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":168,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[168]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":168,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[168]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":168,\"outFeatures\":41}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 3987-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2556\nComponents:\n - input (input) params={\"shape\":[1,54]}\n - fc1 (linear) params={\"inFeatures\":54,\"outFeatures\":3987}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3987,\"outFeatures\":3987}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":3987,\"outFeatures\":29}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":54,\"outFeatures\":90}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":90,\"outFeatures\":90}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":90,\"outFeatures\":29}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 239-feature, 83-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2557\nComponents:\n - input (input) params={\"shape\":[1,239]}\n - fc1 (linear) params={\"inFeatures\":239,\"outFeatures\":498}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":498,\"outFeatures\":150}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":150,\"outFeatures\":83}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":498}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":150}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 105-feature user input and a 140-feature item input, each through its own 2-layer MLP tower ending at width 451, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2558\nComponents:\n - user_input (input) params={\"shape\":[1,105]}\n - item_input (input) params={\"shape\":[1,140]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,105]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,140]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":105,\"outFeatures\":451}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":451,\"outFeatures\":451}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":140,\"outFeatures\":451}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":451,\"outFeatures\":451}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":902,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (88-feature input, 11 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2559\nComponents:\n - input (input) params={\"shape\":[1,88]}\n - fc1 (linear) params={\"inFeatures\":88,\"outFeatures\":19}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":19,\"outFeatures\":19}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":19,\"outFeatures\":11}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":88,\"outFeatures\":647}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":647,\"outFeatures\":647}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":647,\"outFeatures\":11}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 439-feature input with 132 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2560\nComponents:\n - input (input) params={\"shape\":[1,439]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,439]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":439,\"outFeatures\":266}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":266,\"outFeatures\":364}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":364,\"outFeatures\":132}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 731-dim input: encode down to a 168-dim bottleneck and decode back to 731. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2561\nComponents:\n - input (input) params={\"shape\":[1,731]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,731]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":731,\"outFeatures\":902}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":902,\"outFeatures\":168}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":168,\"outFeatures\":902}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":902,\"outFeatures\":731}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x36x36 image with 80 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2562\nComponents:\n - input (input) params={\"shape\":[1,3,36,36]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,36,36]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":47,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":47,\"outChannels\":35,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":35,\"outChannels\":24,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":24,\"outChannels\":24,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":24,\"outFeatures\":80}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 132-token sequences with 24 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2563\nComponents:\n - input (input) params={\"shape\":[1,132]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,132]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":20358,\"embeddingDim\":128}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":128,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":128,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":128,\"outFeatures\":24}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 228-token sequences with 23 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2564\nComponents:\n - input (input) params={\"shape\":[1,228]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,228]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":10401,\"embeddingDim\":368}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":368,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[368]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":368,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[368]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":368,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[368]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":368,\"outFeatures\":23}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (316) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-2565\nComponents:\n - input (input) params={\"shape\":[1,287]}\n - embed (embedding) params={\"numEmbeddings\":18982,\"embeddingDim\":316}\n - attn (multiHeadAttention) params={\"embedDim\":316,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":316,\"outFeatures\":47}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":4}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 2742-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2566\nComponents:\n - input (input) params={\"shape\":[1,88]}\n - fc1 (linear) params={\"inFeatures\":88,\"outFeatures\":2742}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2742,\"outFeatures\":2742}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":2742,\"outFeatures\":20}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":88,\"outFeatures\":352}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":352,\"outFeatures\":352}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":352,\"outFeatures\":20}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 98-feature, 60-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2567\nComponents:\n - input (input) params={\"shape\":[1,98]}\n - fc1 (linear) params={\"inFeatures\":98,\"outFeatures\":301}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":301,\"outFeatures\":383}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":383,\"outFeatures\":60}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":301}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":383}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 153-feature user input and a 196-feature item input, each through its own 2-layer MLP tower ending at width 437, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2568\nComponents:\n - user_input (input) params={\"shape\":[1,153]}\n - item_input (input) params={\"shape\":[1,196]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,153]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,196]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":153,\"outFeatures\":437}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":437,\"outFeatures\":437}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":196,\"outFeatures\":437}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":437,\"outFeatures\":437}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":874,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (32-feature input, 41 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2569\nComponents:\n - input (input) params={\"shape\":[1,32]}\n - fc1 (linear) params={\"inFeatures\":32,\"outFeatures\":20}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":20,\"outFeatures\":20}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":20,\"outFeatures\":41}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":32,\"outFeatures\":1279}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1279,\"outFeatures\":1279}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1279,\"outFeatures\":41}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 237-feature input with 174 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2570\nComponents:\n - input (input) params={\"shape\":[1,237]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,237]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":237,\"outFeatures\":542}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":542,\"outFeatures\":801}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":801,\"outFeatures\":174}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1269-dim input: encode down to a 97-dim bottleneck and decode back to 1269. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2571\nComponents:\n - input (input) params={\"shape\":[1,1269]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1269]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1269,\"outFeatures\":853}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":853,\"outFeatures\":97}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":97,\"outFeatures\":853}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":853,\"outFeatures\":1269}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x41x41 image with 43 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2572\nComponents:\n - input (input) params={\"shape\":[1,3,41,41]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,41,41]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":14,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":14,\"outChannels\":57,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":57,\"outChannels\":11,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":11,\"outChannels\":61,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":61,\"outFeatures\":43}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 57-token sequences with 23 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2573\nComponents:\n - input (input) params={\"shape\":[1,57]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,57]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":24754,\"embeddingDim\":240}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":240,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":240,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":240,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":240,\"outFeatures\":23}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 55-token sequences with 72 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2574\nComponents:\n - input (input) params={\"shape\":[1,55]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,55]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":36819,\"embeddingDim\":104}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":104,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[104]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":104,\"outFeatures\":72}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3640-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2576\nComponents:\n - input (input) params={\"shape\":[1,186]}\n - fc1 (linear) params={\"inFeatures\":186,\"outFeatures\":3640}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3640,\"outFeatures\":3640}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3640,\"outFeatures\":3640}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3640,\"outFeatures\":3640}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3640,\"outFeatures\":20}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":186,\"outFeatures\":238}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":238,\"outFeatures\":238}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":238,\"outFeatures\":238}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":238,\"outFeatures\":238}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":238,\"outFeatures\":20}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 217-feature, 14-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2577\nComponents:\n - input (input) params={\"shape\":[1,217]}\n - fc1 (linear) params={\"inFeatures\":217,\"outFeatures\":84}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":84,\"outFeatures\":133}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":133,\"outFeatures\":14}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":84}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":133}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 89-feature user input and a 171-feature item input, each through its own 2-layer MLP tower ending at width 151, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2578\nComponents:\n - user_input (input) params={\"shape\":[1,89]}\n - item_input (input) params={\"shape\":[1,171]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,89]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,171]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":89,\"outFeatures\":151}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":151,\"outFeatures\":151}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":171,\"outFeatures\":151}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":151,\"outFeatures\":151}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":302,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (60-feature input, 14 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2579\nComponents:\n - input (input) params={\"shape\":[1,60]}\n - fc1 (linear) params={\"inFeatures\":60,\"outFeatures\":17}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":17,\"outFeatures\":17}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":17,\"outFeatures\":14}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":60,\"outFeatures\":798}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":798,\"outFeatures\":798}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":798,\"outFeatures\":14}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 328-feature input with 2 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2580\nComponents:\n - input (input) params={\"shape\":[1,328]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,328]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":328,\"outFeatures\":49}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":49,\"outFeatures\":969}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":969,\"outFeatures\":820}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":820,\"outFeatures\":2}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 933-dim input: encode down to a 125-dim bottleneck and decode back to 933. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2581\nComponents:\n - input (input) params={\"shape\":[1,933]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,933]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":933,\"outFeatures\":1003}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":1003,\"outFeatures\":125}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":125,\"outFeatures\":1003}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":1003,\"outFeatures\":933}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x53x53 image with 69 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2582\nComponents:\n - input (input) params={\"shape\":[1,3,53,53]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,53,53]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":26,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":26,\"outChannels\":37,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":37,\"outChannels\":45,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":45,\"outChannels\":49,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":49,\"outFeatures\":69}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 442-token sequences with 23 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2583\nComponents:\n - input (input) params={\"shape\":[1,442]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,442]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":18020,\"embeddingDim\":272}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":272,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":272,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":272,\"outFeatures\":23}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 129-token sequences with 77 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2584\nComponents:\n - input (input) params={\"shape\":[1,129]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,129]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":27036,\"embeddingDim\":216}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":216,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[216]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":216,\"outFeatures\":77}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (94) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-2585\nComponents:\n - input (input) params={\"shape\":[1,478]}\n - embed (embedding) params={\"numEmbeddings\":48201,\"embeddingDim\":94}\n - attn (multiHeadAttention) params={\"embedDim\":94,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":94,\"outFeatures\":13}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 2831-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2586\nComponents:\n - input (input) params={\"shape\":[1,117]}\n - fc1 (linear) params={\"inFeatures\":117,\"outFeatures\":2831}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2831,\"outFeatures\":2831}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":2831,\"outFeatures\":27}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":117,\"outFeatures\":229}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":229,\"outFeatures\":229}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":229,\"outFeatures\":27}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 105-feature, 54-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2587\nComponents:\n - input (input) params={\"shape\":[1,105]}\n - fc1 (linear) params={\"inFeatures\":105,\"outFeatures\":176}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":176,\"outFeatures\":273}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":273,\"outFeatures\":65}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":65,\"outFeatures\":479}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":479,\"outFeatures\":149}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":149,\"outFeatures\":54}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":176}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":273}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":65}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":479}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":149}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 206-feature user input and a 80-feature item input, each through its own 2-layer MLP tower ending at width 424, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2588\nComponents:\n - user_input (input) params={\"shape\":[1,206]}\n - item_input (input) params={\"shape\":[1,80]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,206]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,80]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":206,\"outFeatures\":424}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":424,\"outFeatures\":424}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":80,\"outFeatures\":424}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":424,\"outFeatures\":424}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":848,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (43-feature input, 10 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2589\nComponents:\n - input (input) params={\"shape\":[1,43]}\n - fc1 (linear) params={\"inFeatures\":43,\"outFeatures\":4}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":4,\"outFeatures\":4}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":4,\"outFeatures\":10}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":43,\"outFeatures\":1109}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1109,\"outFeatures\":1109}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1109,\"outFeatures\":10}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 57-feature input with 188 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2590\nComponents:\n - input (input) params={\"shape\":[1,57]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,57]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":57,\"outFeatures\":272}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":272,\"outFeatures\":154}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":154,\"outFeatures\":793}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":793,\"outFeatures\":326}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":326,\"outFeatures\":220}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":220,\"outFeatures\":679}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":679,\"outFeatures\":188}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1864-dim input: encode down to a 113-dim bottleneck and decode back to 1864. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2591\nComponents:\n - input (input) params={\"shape\":[1,1864]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1864]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1864,\"outFeatures\":634}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":634,\"outFeatures\":113}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":113,\"outFeatures\":634}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":634,\"outFeatures\":1864}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x53x53 image with 28 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2592\nComponents:\n - input (input) params={\"shape\":[1,3,53,53]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,53,53]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":62,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":62,\"outChannels\":40,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":40,\"outChannels\":64,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":64,\"outChannels\":60,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":60,\"outFeatures\":28}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 116-token sequences with 60 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2593\nComponents:\n - input (input) params={\"shape\":[1,116]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,116]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":46494,\"embeddingDim\":288}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":288,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":288,\"outFeatures\":60}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 279-token sequences with 77 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2594\nComponents:\n - input (input) params={\"shape\":[1,279]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,279]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":37991,\"embeddingDim\":384}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":384,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[384]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":384,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[384]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":384,\"outFeatures\":77}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (362) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-2595\nComponents:\n - input (input) params={\"shape\":[1,159]}\n - embed (embedding) params={\"numEmbeddings\":34105,\"embeddingDim\":362}\n - attn (multiHeadAttention) params={\"embedDim\":362,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":362,\"outFeatures\":39}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 3631-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2596\nComponents:\n - input (input) params={\"shape\":[1,123]}\n - fc1 (linear) params={\"inFeatures\":123,\"outFeatures\":3631}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3631,\"outFeatures\":3631}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":3631,\"outFeatures\":4}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":123,\"outFeatures\":270}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":270,\"outFeatures\":270}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":270,\"outFeatures\":4}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 162-feature, 26-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2597\nComponents:\n - input (input) params={\"shape\":[1,162]}\n - fc1 (linear) params={\"inFeatures\":162,\"outFeatures\":141}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":141,\"outFeatures\":69}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":69,\"outFeatures\":26}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":141}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":69}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 171-feature user input and a 111-feature item input, each through its own 2-layer MLP tower ending at width 365, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2598\nComponents:\n - user_input (input) params={\"shape\":[1,171]}\n - item_input (input) params={\"shape\":[1,111]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,171]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,111]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":171,\"outFeatures\":365}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":365,\"outFeatures\":365}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":111,\"outFeatures\":365}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":365,\"outFeatures\":365}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":730,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (105-feature input, 24 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2599\nComponents:\n - input (input) params={\"shape\":[1,105]}\n - fc1 (linear) params={\"inFeatures\":105,\"outFeatures\":22}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":22,\"outFeatures\":22}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":22,\"outFeatures\":24}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":105,\"outFeatures\":659}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":659,\"outFeatures\":659}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":659,\"outFeatures\":24}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 257-feature input with 144 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2600\nComponents:\n - input (input) params={\"shape\":[1,257]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,257]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":257,\"outFeatures\":183}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":183,\"outFeatures\":668}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":668,\"outFeatures\":480}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":480,\"outFeatures\":441}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":441,\"outFeatures\":765}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":765,\"outFeatures\":144}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1368-dim input: encode down to a 181-dim bottleneck and decode back to 1368. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2601\nComponents:\n - input (input) params={\"shape\":[1,1368]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1368]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1368,\"outFeatures\":789}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":789,\"outFeatures\":181}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":181,\"outFeatures\":789}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":789,\"outFeatures\":1368}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x40x40 image with 85 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2602\nComponents:\n - input (input) params={\"shape\":[1,3,40,40]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,40,40]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":62,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":62,\"outChannels\":13,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":13,\"outChannels\":59,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":59,\"outChannels\":58,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":58,\"outFeatures\":85}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 284-token sequences with 71 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2603\nComponents:\n - input (input) params={\"shape\":[1,284]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,284]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":32587,\"embeddingDim\":72}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":72,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":72,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":72,\"outFeatures\":71}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 374-token sequences with 5 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2604\nComponents:\n - input (input) params={\"shape\":[1,374]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,374]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":17534,\"embeddingDim\":304}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":304,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[304]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":304,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[304]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":304,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[304]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":304,\"outFeatures\":5}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 3238-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2606\nComponents:\n - input (input) params={\"shape\":[1,51]}\n - fc1 (linear) params={\"inFeatures\":51,\"outFeatures\":3238}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3238,\"outFeatures\":3238}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3238,\"outFeatures\":3238}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":3238,\"outFeatures\":23}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":51,\"outFeatures\":360}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":360,\"outFeatures\":360}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":360,\"outFeatures\":360}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":360,\"outFeatures\":23}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 98-feature, 74-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2607\nComponents:\n - input (input) params={\"shape\":[1,98]}\n - fc1 (linear) params={\"inFeatures\":98,\"outFeatures\":421}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":421,\"outFeatures\":440}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":440,\"outFeatures\":74}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":421}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":440}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 53-feature user input and a 166-feature item input, each through its own 2-layer MLP tower ending at width 323, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2608\nComponents:\n - user_input (input) params={\"shape\":[1,53]}\n - item_input (input) params={\"shape\":[1,166]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,53]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,166]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":53,\"outFeatures\":323}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":323,\"outFeatures\":323}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":166,\"outFeatures\":323}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":323,\"outFeatures\":323}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":646,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (60-feature input, 8 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2609\nComponents:\n - input (input) params={\"shape\":[1,60]}\n - fc1 (linear) params={\"inFeatures\":60,\"outFeatures\":12}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":12,\"outFeatures\":12}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":12,\"outFeatures\":8}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":60,\"outFeatures\":954}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":954,\"outFeatures\":954}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":954,\"outFeatures\":8}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 251-feature input with 137 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2610\nComponents:\n - input (input) params={\"shape\":[1,251]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,251]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":251,\"outFeatures\":296}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":296,\"outFeatures\":744}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":744,\"outFeatures\":437}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":437,\"outFeatures\":107}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":107,\"outFeatures\":137}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 258-dim input: encode down to a 52-dim bottleneck and decode back to 258. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2611\nComponents:\n - input (input) params={\"shape\":[1,258]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,258]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":258,\"outFeatures\":1016}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":1016,\"outFeatures\":52}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":52,\"outFeatures\":1016}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":1016,\"outFeatures\":258}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x43x43 image with 41 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2612\nComponents:\n - input (input) params={\"shape\":[1,3,43,43]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,43,43]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":58,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":58,\"outChannels\":30,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":30,\"outChannels\":25,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":25,\"outChannels\":24,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":24,\"outFeatures\":41}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 93-token sequences with 58 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2613\nComponents:\n - input (input) params={\"shape\":[1,93]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,93]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":33991,\"embeddingDim\":76}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":76,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":76,\"outFeatures\":58}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 480-token sequences with 86 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2614\nComponents:\n - input (input) params={\"shape\":[1,480]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,480]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":34339,\"embeddingDim\":496}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":496,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[496]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":496,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[496]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":496,\"outFeatures\":86}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 3085-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2616\nComponents:\n - input (input) params={\"shape\":[1,139]}\n - fc1 (linear) params={\"inFeatures\":139,\"outFeatures\":3085}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3085,\"outFeatures\":3085}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":3085,\"outFeatures\":8}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":139,\"outFeatures\":188}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":188,\"outFeatures\":188}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":188,\"outFeatures\":8}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 196-feature, 78-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2617\nComponents:\n - input (input) params={\"shape\":[1,196]}\n - fc1 (linear) params={\"inFeatures\":196,\"outFeatures\":261}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":261,\"outFeatures\":217}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":217,\"outFeatures\":78}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":261}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":217}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 173-feature user input and a 118-feature item input, each through its own 2-layer MLP tower ending at width 486, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2618\nComponents:\n - user_input (input) params={\"shape\":[1,173]}\n - item_input (input) params={\"shape\":[1,118]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,173]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,118]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":173,\"outFeatures\":486}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":486,\"outFeatures\":486}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":118,\"outFeatures\":486}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":486,\"outFeatures\":486}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":972,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (71-feature input, 12 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2619\nComponents:\n - input (input) params={\"shape\":[1,71]}\n - fc1 (linear) params={\"inFeatures\":71,\"outFeatures\":23}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":23,\"outFeatures\":23}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":23,\"outFeatures\":12}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":71,\"outFeatures\":1156}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1156,\"outFeatures\":1156}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1156,\"outFeatures\":12}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 228-feature input with 171 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2620\nComponents:\n - input (input) params={\"shape\":[1,228]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,228]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":228,\"outFeatures\":43}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":43,\"outFeatures\":521}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":521,\"outFeatures\":321}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":321,\"outFeatures\":749}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":749,\"outFeatures\":171}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 849-dim input: encode down to a 149-dim bottleneck and decode back to 849. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2621\nComponents:\n - input (input) params={\"shape\":[1,849]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,849]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":849,\"outFeatures\":603}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":603,\"outFeatures\":149}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":149,\"outFeatures\":603}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":603,\"outFeatures\":849}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x49x49 image with 40 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2622\nComponents:\n - input (input) params={\"shape\":[1,3,49,49]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,49,49]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":24,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":24,\"outChannels\":21,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":21,\"outChannels\":10,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":10,\"outChannels\":20,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":20,\"outFeatures\":40}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 254-token sequences with 7 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2623\nComponents:\n - input (input) params={\"shape\":[1,254]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,254]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":31435,\"embeddingDim\":152}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":152,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":152,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":152,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":152,\"outFeatures\":7}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 265-token sequences with 51 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2624\nComponents:\n - input (input) params={\"shape\":[1,265]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,265]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":42658,\"embeddingDim\":144}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":144,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[144]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":144,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[144]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":144,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[144]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":144,\"outFeatures\":51}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (352) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-2625\nComponents:\n - input (input) params={\"shape\":[1,242]}\n - embed (embedding) params={\"numEmbeddings\":48727,\"embeddingDim\":352}\n - attn (multiHeadAttention) params={\"embedDim\":352,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":352,\"outFeatures\":57}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":16}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 1716-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2626\nComponents:\n - input (input) params={\"shape\":[1,98]}\n - fc1 (linear) params={\"inFeatures\":98,\"outFeatures\":1716}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":1716,\"outFeatures\":1716}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":1716,\"outFeatures\":1716}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":1716,\"outFeatures\":1716}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":1716,\"outFeatures\":7}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":98,\"outFeatures\":242}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":242,\"outFeatures\":242}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":242,\"outFeatures\":242}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":242,\"outFeatures\":242}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":242,\"outFeatures\":7}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 61-feature, 97-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2627\nComponents:\n - input (input) params={\"shape\":[1,61]}\n - fc1 (linear) params={\"inFeatures\":61,\"outFeatures\":388}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":388,\"outFeatures\":41}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":41,\"outFeatures\":211}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":211,\"outFeatures\":349}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":349,\"outFeatures\":97}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":388}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":41}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":211}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":349}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 119-feature user input and a 87-feature item input, each through its own 2-layer MLP tower ending at width 153, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2628\nComponents:\n - user_input (input) params={\"shape\":[1,119]}\n - item_input (input) params={\"shape\":[1,87]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,119]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,87]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":119,\"outFeatures\":153}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":153,\"outFeatures\":153}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":87,\"outFeatures\":153}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":153,\"outFeatures\":153}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":306,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (106-feature input, 8 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2629\nComponents:\n - input (input) params={\"shape\":[1,106]}\n - fc1 (linear) params={\"inFeatures\":106,\"outFeatures\":18}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":18,\"outFeatures\":18}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":18,\"outFeatures\":8}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":106,\"outFeatures\":1040}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1040,\"outFeatures\":1040}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1040,\"outFeatures\":8}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 511-feature input with 172 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2630\nComponents:\n - input (input) params={\"shape\":[1,511]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,511]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":511,\"outFeatures\":957}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":957,\"outFeatures\":383}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":383,\"outFeatures\":295}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":295,\"outFeatures\":800}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":800,\"outFeatures\":618}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":618,\"outFeatures\":104}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":104,\"outFeatures\":172}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 675-dim input: encode down to a 134-dim bottleneck and decode back to 675. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2631\nComponents:\n - input (input) params={\"shape\":[1,675]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,675]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":675,\"outFeatures\":721}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":721,\"outFeatures\":134}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":134,\"outFeatures\":721}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":721,\"outFeatures\":675}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x41x41 image with 32 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2632\nComponents:\n - input (input) params={\"shape\":[1,3,41,41]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,41,41]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":25,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":25,\"outChannels\":63,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":63,\"outChannels\":42,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":42,\"outFeatures\":32}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 449-token sequences with 99 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2633\nComponents:\n - input (input) params={\"shape\":[1,449]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,449]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":29755,\"embeddingDim\":240}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":240,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":240,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":240,\"outFeatures\":99}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 321-token sequences with 54 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2634\nComponents:\n - input (input) params={\"shape\":[1,321]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,321]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":21483,\"embeddingDim\":160}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":160,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[160]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":160,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[160]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":160,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[160]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":160,\"outFeatures\":54}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 3247-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2636\nComponents:\n - input (input) params={\"shape\":[1,104]}\n - fc1 (linear) params={\"inFeatures\":104,\"outFeatures\":3247}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3247,\"outFeatures\":3247}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3247,\"outFeatures\":3247}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":3247,\"outFeatures\":49}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":104,\"outFeatures\":209}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":209,\"outFeatures\":209}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":209,\"outFeatures\":209}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":209,\"outFeatures\":49}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 113-feature, 72-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2637\nComponents:\n - input (input) params={\"shape\":[1,113]}\n - fc1 (linear) params={\"inFeatures\":113,\"outFeatures\":443}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":443,\"outFeatures\":152}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":152,\"outFeatures\":89}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":89,\"outFeatures\":72}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":443}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":152}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":89}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 142-feature user input and a 67-feature item input, each through its own 2-layer MLP tower ending at width 465, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2638\nComponents:\n - user_input (input) params={\"shape\":[1,142]}\n - item_input (input) params={\"shape\":[1,67]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,142]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,67]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":142,\"outFeatures\":465}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":465,\"outFeatures\":465}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":67,\"outFeatures\":465}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":465,\"outFeatures\":465}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":930,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (106-feature input, 28 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2639\nComponents:\n - input (input) params={\"shape\":[1,106]}\n - fc1 (linear) params={\"inFeatures\":106,\"outFeatures\":20}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":20,\"outFeatures\":20}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":20,\"outFeatures\":28}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":106,\"outFeatures\":669}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":669,\"outFeatures\":669}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":669,\"outFeatures\":28}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 346-feature input with 170 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2640\nComponents:\n - input (input) params={\"shape\":[1,346]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,346]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":346,\"outFeatures\":839}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":839,\"outFeatures\":927}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":927,\"outFeatures\":200}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":200,\"outFeatures\":170}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 668-dim input: encode down to a 178-dim bottleneck and decode back to 668. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2641\nComponents:\n - input (input) params={\"shape\":[1,668]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,668]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":668,\"outFeatures\":981}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":981,\"outFeatures\":178}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":178,\"outFeatures\":981}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":981,\"outFeatures\":668}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x45x45 image with 61 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2642\nComponents:\n - input (input) params={\"shape\":[1,3,45,45]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,45,45]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":19,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":19,\"outChannels\":54,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":54,\"outChannels\":44,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":44,\"outChannels\":33,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":33,\"outFeatures\":61}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 219-token sequences with 32 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2643\nComponents:\n - input (input) params={\"shape\":[1,219]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,219]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":39910,\"embeddingDim\":36}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":36,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":36,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":36,\"outFeatures\":32}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 335-token sequences with 13 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2644\nComponents:\n - input (input) params={\"shape\":[1,335]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,335]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":9196,\"embeddingDim\":160}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":160,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[160]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":160,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[160]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":160,\"outFeatures\":13}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (398) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-2645\nComponents:\n - input (input) params={\"shape\":[1,221]}\n - embed (embedding) params={\"numEmbeddings\":42753,\"embeddingDim\":398}\n - attn (multiHeadAttention) params={\"embedDim\":398,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":398,\"outFeatures\":60}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 1719-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2646\nComponents:\n - input (input) params={\"shape\":[1,53]}\n - fc1 (linear) params={\"inFeatures\":53,\"outFeatures\":1719}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":1719,\"outFeatures\":1719}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":1719,\"outFeatures\":40}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":53,\"outFeatures\":213}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":213,\"outFeatures\":213}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":213,\"outFeatures\":40}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 154-feature, 88-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2647\nComponents:\n - input (input) params={\"shape\":[1,154]}\n - fc1 (linear) params={\"inFeatures\":154,\"outFeatures\":45}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":45,\"outFeatures\":150}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":150,\"outFeatures\":52}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":52,\"outFeatures\":61}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":61,\"outFeatures\":384}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":384,\"outFeatures\":88}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":45}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":150}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":52}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":61}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":384}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 138-feature user input and a 44-feature item input, each through its own 2-layer MLP tower ending at width 193, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2648\nComponents:\n - user_input (input) params={\"shape\":[1,138]}\n - item_input (input) params={\"shape\":[1,44]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,138]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,44]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":138,\"outFeatures\":193}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":193,\"outFeatures\":193}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":44,\"outFeatures\":193}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":193,\"outFeatures\":193}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":386,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (115-feature input, 41 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2649\nComponents:\n - input (input) params={\"shape\":[1,115]}\n - fc1 (linear) params={\"inFeatures\":115,\"outFeatures\":24}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":24,\"outFeatures\":24}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":24,\"outFeatures\":41}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":115,\"outFeatures\":1037}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1037,\"outFeatures\":1037}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1037,\"outFeatures\":41}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 443-feature input with 105 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2650\nComponents:\n - input (input) params={\"shape\":[1,443]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,443]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":443,\"outFeatures\":912}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":912,\"outFeatures\":30}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":30,\"outFeatures\":105}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1161-dim input: encode down to a 114-dim bottleneck and decode back to 1161. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2651\nComponents:\n - input (input) params={\"shape\":[1,1161]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1161]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1161,\"outFeatures\":464}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":464,\"outFeatures\":114}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":114,\"outFeatures\":464}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":464,\"outFeatures\":1161}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x59x59 image with 62 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2652\nComponents:\n - input (input) params={\"shape\":[1,3,59,59]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,59,59]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":43,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":43,\"outChannels\":52,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":52,\"outChannels\":55,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":55,\"outChannels\":31,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":31,\"outFeatures\":62}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 151-token sequences with 80 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2653\nComponents:\n - input (input) params={\"shape\":[1,151]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,151]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":48968,\"embeddingDim\":496}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":496,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":496,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":496,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":496,\"outFeatures\":80}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 391-token sequences with 19 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2654\nComponents:\n - input (input) params={\"shape\":[1,391]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,391]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":33284,\"embeddingDim\":136}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":136,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[136]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":136,\"outFeatures\":19}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 2142-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2656\nComponents:\n - input (input) params={\"shape\":[1,164]}\n - fc1 (linear) params={\"inFeatures\":164,\"outFeatures\":2142}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2142,\"outFeatures\":2142}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":2142,\"outFeatures\":2}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":164,\"outFeatures\":190}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":190,\"outFeatures\":190}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":190,\"outFeatures\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 218-feature, 53-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2657\nComponents:\n - input (input) params={\"shape\":[1,218]}\n - fc1 (linear) params={\"inFeatures\":218,\"outFeatures\":460}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":460,\"outFeatures\":56}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":56,\"outFeatures\":260}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":260,\"outFeatures\":53}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":460}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":56}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":260}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 58-feature user input and a 247-feature item input, each through its own 2-layer MLP tower ending at width 410, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2658\nComponents:\n - user_input (input) params={\"shape\":[1,58]}\n - item_input (input) params={\"shape\":[1,247]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,58]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,247]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":58,\"outFeatures\":410}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":410,\"outFeatures\":410}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":247,\"outFeatures\":410}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":410,\"outFeatures\":410}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":820,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (76-feature input, 26 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2659\nComponents:\n - input (input) params={\"shape\":[1,76]}\n - fc1 (linear) params={\"inFeatures\":76,\"outFeatures\":13}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":13,\"outFeatures\":13}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":13,\"outFeatures\":26}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":76,\"outFeatures\":791}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":791,\"outFeatures\":791}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":791,\"outFeatures\":26}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 301-feature input with 180 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2660\nComponents:\n - input (input) params={\"shape\":[1,301]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,301]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":301,\"outFeatures\":623}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":623,\"outFeatures\":858}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":858,\"outFeatures\":318}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":318,\"outFeatures\":52}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":52,\"outFeatures\":180}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1195-dim input: encode down to a 13-dim bottleneck and decode back to 1195. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2661\nComponents:\n - input (input) params={\"shape\":[1,1195]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1195]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1195,\"outFeatures\":420}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":420,\"outFeatures\":13}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":13,\"outFeatures\":420}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":420,\"outFeatures\":1195}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x35x35 image with 75 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2662\nComponents:\n - input (input) params={\"shape\":[1,3,35,35]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,35,35]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":37,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":37,\"outChannels\":58,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":58,\"outChannels\":26,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":26,\"outChannels\":46,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":46,\"outFeatures\":75}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 358-token sequences with 31 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2663\nComponents:\n - input (input) params={\"shape\":[1,358]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,358]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":9093,\"embeddingDim\":32}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":32,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":32,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":32,\"outFeatures\":31}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 222-token sequences with 42 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2664\nComponents:\n - input (input) params={\"shape\":[1,222]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,222]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":18560,\"embeddingDim\":272}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":272,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[272]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":272,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[272]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":272,\"outFeatures\":42}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 2852-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2666\nComponents:\n - input (input) params={\"shape\":[1,192]}\n - fc1 (linear) params={\"inFeatures\":192,\"outFeatures\":2852}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2852,\"outFeatures\":2852}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":2852,\"outFeatures\":34}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":192,\"outFeatures\":261}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":261,\"outFeatures\":261}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":261,\"outFeatures\":34}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 124-feature, 92-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2667\nComponents:\n - input (input) params={\"shape\":[1,124]}\n - fc1 (linear) params={\"inFeatures\":124,\"outFeatures\":454}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":454,\"outFeatures\":394}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":394,\"outFeatures\":125}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":125,\"outFeatures\":435}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":435,\"outFeatures\":366}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":366,\"outFeatures\":92}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":454}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":394}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":125}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":435}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":366}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 149-feature user input and a 156-feature item input, each through its own 2-layer MLP tower ending at width 328, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2668\nComponents:\n - user_input (input) params={\"shape\":[1,149]}\n - item_input (input) params={\"shape\":[1,156]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,149]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,156]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":149,\"outFeatures\":328}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":328,\"outFeatures\":328}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":156,\"outFeatures\":328}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":328,\"outFeatures\":328}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":656,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (30-feature input, 45 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2669\nComponents:\n - input (input) params={\"shape\":[1,30]}\n - fc1 (linear) params={\"inFeatures\":30,\"outFeatures\":24}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":24,\"outFeatures\":24}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":24,\"outFeatures\":45}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":30,\"outFeatures\":830}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":830,\"outFeatures\":830}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":830,\"outFeatures\":45}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 274-feature input with 57 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2670\nComponents:\n - input (input) params={\"shape\":[1,274]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,274]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":274,\"outFeatures\":999}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":999,\"outFeatures\":175}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":175,\"outFeatures\":64}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":64,\"outFeatures\":469}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":469,\"outFeatures\":57}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 151-dim input: encode down to a 215-dim bottleneck and decode back to 151. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2671\nComponents:\n - input (input) params={\"shape\":[1,151]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,151]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":151,\"outFeatures\":918}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":918,\"outFeatures\":215}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":215,\"outFeatures\":918}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":918,\"outFeatures\":151}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x46x46 image with 46 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2672\nComponents:\n - input (input) params={\"shape\":[1,3,46,46]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,46,46]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":52,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":52,\"outChannels\":15,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":15,\"outChannels\":39,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":39,\"outFeatures\":46}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 372-token sequences with 85 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2673\nComponents:\n - input (input) params={\"shape\":[1,372]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,372]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":15746,\"embeddingDim\":40}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":40,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":40,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":40,\"outFeatures\":85}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 282-token sequences with 64 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2674\nComponents:\n - input (input) params={\"shape\":[1,282]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,282]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":10276,\"embeddingDim\":164}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":164,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[164]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":164,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[164]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":164,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[164]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":164,\"outFeatures\":64}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 4043-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2676\nComponents:\n - input (input) params={\"shape\":[1,186]}\n - fc1 (linear) params={\"inFeatures\":186,\"outFeatures\":4043}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":4043,\"outFeatures\":4043}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":4043,\"outFeatures\":4043}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":4043,\"outFeatures\":4043}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":4043,\"outFeatures\":36}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":186,\"outFeatures\":319}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":319,\"outFeatures\":319}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":319,\"outFeatures\":319}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":319,\"outFeatures\":319}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":319,\"outFeatures\":36}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 47-feature, 72-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2677\nComponents:\n - input (input) params={\"shape\":[1,47]}\n - fc1 (linear) params={\"inFeatures\":47,\"outFeatures\":323}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":323,\"outFeatures\":147}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":147,\"outFeatures\":72}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":323}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":147}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 41-feature user input and a 88-feature item input, each through its own 2-layer MLP tower ending at width 174, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2678\nComponents:\n - user_input (input) params={\"shape\":[1,41]}\n - item_input (input) params={\"shape\":[1,88]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,41]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,88]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":41,\"outFeatures\":174}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":174,\"outFeatures\":174}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":88,\"outFeatures\":174}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":174,\"outFeatures\":174}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":348,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (115-feature input, 20 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2679\nComponents:\n - input (input) params={\"shape\":[1,115]}\n - fc1 (linear) params={\"inFeatures\":115,\"outFeatures\":19}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":19,\"outFeatures\":19}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":19,\"outFeatures\":20}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":115,\"outFeatures\":962}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":962,\"outFeatures\":962}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":962,\"outFeatures\":20}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 488-feature input with 28 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2680\nComponents:\n - input (input) params={\"shape\":[1,488]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,488]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":488,\"outFeatures\":930}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":930,\"outFeatures\":418}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":418,\"outFeatures\":67}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":67,\"outFeatures\":28}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 495-dim input: encode down to a 109-dim bottleneck and decode back to 495. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2681\nComponents:\n - input (input) params={\"shape\":[1,495]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,495]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":495,\"outFeatures\":610}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":610,\"outFeatures\":109}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":109,\"outFeatures\":610}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":610,\"outFeatures\":495}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x27x27 image with 91 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2682\nComponents:\n - input (input) params={\"shape\":[1,3,27,27]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,27,27]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":21,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":21,\"outChannels\":40,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":40,\"outChannels\":51,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":51,\"outChannels\":56,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":56,\"outFeatures\":91}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 288-token sequences with 16 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2683\nComponents:\n - input (input) params={\"shape\":[1,288]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,288]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":41958,\"embeddingDim\":344}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":344,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":344,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":344,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":344,\"outFeatures\":16}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 89-token sequences with 71 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2684\nComponents:\n - input (input) params={\"shape\":[1,89]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,89]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":41641,\"embeddingDim\":88}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":88,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[88]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":88,\"outFeatures\":71}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 3486-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2686\nComponents:\n - input (input) params={\"shape\":[1,115]}\n - fc1 (linear) params={\"inFeatures\":115,\"outFeatures\":3486}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3486,\"outFeatures\":3486}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3486,\"outFeatures\":3486}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":3486,\"outFeatures\":31}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":115,\"outFeatures\":332}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":332,\"outFeatures\":332}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":332,\"outFeatures\":332}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":332,\"outFeatures\":31}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 192-feature, 53-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2687\nComponents:\n - input (input) params={\"shape\":[1,192]}\n - fc1 (linear) params={\"inFeatures\":192,\"outFeatures\":298}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":298,\"outFeatures\":123}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":123,\"outFeatures\":53}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":298}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":123}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 118-feature user input and a 240-feature item input, each through its own 2-layer MLP tower ending at width 259, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2688\nComponents:\n - user_input (input) params={\"shape\":[1,118]}\n - item_input (input) params={\"shape\":[1,240]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,118]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,240]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":118,\"outFeatures\":259}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":259,\"outFeatures\":259}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":240,\"outFeatures\":259}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":259,\"outFeatures\":259}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":518,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (76-feature input, 45 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2689\nComponents:\n - input (input) params={\"shape\":[1,76]}\n - fc1 (linear) params={\"inFeatures\":76,\"outFeatures\":16}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":16,\"outFeatures\":16}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":16,\"outFeatures\":45}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":76,\"outFeatures\":664}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":664,\"outFeatures\":664}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":664,\"outFeatures\":45}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 36-feature input with 26 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2690\nComponents:\n - input (input) params={\"shape\":[1,36]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,36]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":36,\"outFeatures\":363}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":363,\"outFeatures\":276}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":276,\"outFeatures\":34}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":34,\"outFeatures\":270}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":270,\"outFeatures\":751}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":751,\"outFeatures\":26}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 819-dim input: encode down to a 114-dim bottleneck and decode back to 819. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2691\nComponents:\n - input (input) params={\"shape\":[1,819]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,819]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":819,\"outFeatures\":554}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":554,\"outFeatures\":114}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":114,\"outFeatures\":554}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":554,\"outFeatures\":819}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x27x27 image with 47 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2692\nComponents:\n - input (input) params={\"shape\":[1,3,27,27]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,27,27]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":53,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":53,\"outChannels\":38,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":38,\"outFeatures\":47}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 356-token sequences with 70 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2693\nComponents:\n - input (input) params={\"shape\":[1,356]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,356]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":11917,\"embeddingDim\":272}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":272,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":272,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":272,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":272,\"outFeatures\":70}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 496-token sequences with 100 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2694\nComponents:\n - input (input) params={\"shape\":[1,496]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,496]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":41162,\"embeddingDim\":416}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":416,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[416]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":416,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[416]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":416,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[416]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":416,\"outFeatures\":100}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 2103-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2696\nComponents:\n - input (input) params={\"shape\":[1,87]}\n - fc1 (linear) params={\"inFeatures\":87,\"outFeatures\":2103}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2103,\"outFeatures\":2103}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2103,\"outFeatures\":2103}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":2103,\"outFeatures\":2103}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":2103,\"outFeatures\":42}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":87,\"outFeatures\":231}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":231,\"outFeatures\":231}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":231,\"outFeatures\":231}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":231,\"outFeatures\":231}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":231,\"outFeatures\":42}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 38-feature, 93-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2697\nComponents:\n - input (input) params={\"shape\":[1,38]}\n - fc1 (linear) params={\"inFeatures\":38,\"outFeatures\":159}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":159,\"outFeatures\":409}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":409,\"outFeatures\":93}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":159}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":409}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 240-feature user input and a 26-feature item input, each through its own 2-layer MLP tower ending at width 252, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2698\nComponents:\n - user_input (input) params={\"shape\":[1,240]}\n - item_input (input) params={\"shape\":[1,26]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,240]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,26]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":240,\"outFeatures\":252}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":252,\"outFeatures\":252}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":26,\"outFeatures\":252}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":252,\"outFeatures\":252}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":504,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (30-feature input, 3 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2699\nComponents:\n - input (input) params={\"shape\":[1,30]}\n - fc1 (linear) params={\"inFeatures\":30,\"outFeatures\":13}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":13,\"outFeatures\":13}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":13,\"outFeatures\":3}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":30,\"outFeatures\":1198}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1198,\"outFeatures\":1198}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1198,\"outFeatures\":3}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 132-feature input with 31 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2700\nComponents:\n - input (input) params={\"shape\":[1,132]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,132]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":132,\"outFeatures\":909}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":909,\"outFeatures\":517}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":517,\"outFeatures\":31}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 362-dim input: encode down to a 7-dim bottleneck and decode back to 362. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2701\nComponents:\n - input (input) params={\"shape\":[1,362]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,362]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":362,\"outFeatures\":682}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":682,\"outFeatures\":7}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":7,\"outFeatures\":682}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":682,\"outFeatures\":362}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x59x59 image with 38 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2702\nComponents:\n - input (input) params={\"shape\":[1,3,59,59]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,59,59]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":53,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":53,\"outChannels\":10,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":10,\"outFeatures\":38}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 294-token sequences with 15 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2703\nComponents:\n - input (input) params={\"shape\":[1,294]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,294]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":33284,\"embeddingDim\":220}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":220,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":220,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":220,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":220,\"outFeatures\":15}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 390-token sequences with 93 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2704\nComponents:\n - input (input) params={\"shape\":[1,390]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,390]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":33715,\"embeddingDim\":68}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":68,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[68]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":68,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[68]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":68,\"outFeatures\":93}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (324) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-2705\nComponents:\n - input (input) params={\"shape\":[1,116]}\n - embed (embedding) params={\"numEmbeddings\":23374,\"embeddingDim\":324}\n - attn (multiHeadAttention) params={\"embedDim\":324,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":324,\"outFeatures\":4}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":4}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 3617-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2706\nComponents:\n - input (input) params={\"shape\":[1,58]}\n - fc1 (linear) params={\"inFeatures\":58,\"outFeatures\":3617}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3617,\"outFeatures\":3617}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3617,\"outFeatures\":3617}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":3617,\"outFeatures\":4}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":58,\"outFeatures\":110}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":110,\"outFeatures\":110}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":110,\"outFeatures\":110}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":110,\"outFeatures\":4}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 106-feature, 34-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2707\nComponents:\n - input (input) params={\"shape\":[1,106]}\n - fc1 (linear) params={\"inFeatures\":106,\"outFeatures\":344}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":344,\"outFeatures\":175}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":175,\"outFeatures\":163}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":163,\"outFeatures\":270}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":270,\"outFeatures\":36}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":36,\"outFeatures\":34}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":344}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":175}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":163}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":270}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":36}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 89-feature user input and a 60-feature item input, each through its own 2-layer MLP tower ending at width 466, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2708\nComponents:\n - user_input (input) params={\"shape\":[1,89]}\n - item_input (input) params={\"shape\":[1,60]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,89]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,60]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":89,\"outFeatures\":466}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":466,\"outFeatures\":466}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":60,\"outFeatures\":466}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":466,\"outFeatures\":466}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":932,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (67-feature input, 22 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2709\nComponents:\n - input (input) params={\"shape\":[1,67]}\n - fc1 (linear) params={\"inFeatures\":67,\"outFeatures\":21}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":21,\"outFeatures\":21}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":21,\"outFeatures\":22}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":67,\"outFeatures\":1104}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1104,\"outFeatures\":1104}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1104,\"outFeatures\":22}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 353-feature input with 130 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2710\nComponents:\n - input (input) params={\"shape\":[1,353]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,353]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":353,\"outFeatures\":202}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":202,\"outFeatures\":191}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":191,\"outFeatures\":179}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":179,\"outFeatures\":130}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 273-dim input: encode down to a 222-dim bottleneck and decode back to 273. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2711\nComponents:\n - input (input) params={\"shape\":[1,273]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,273]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":273,\"outFeatures\":660}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":660,\"outFeatures\":222}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":222,\"outFeatures\":660}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":660,\"outFeatures\":273}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x33x33 image with 88 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2712\nComponents:\n - input (input) params={\"shape\":[1,3,33,33]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,33,33]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":13,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":13,\"outChannels\":37,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":37,\"outChannels\":8,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":8,\"outChannels\":22,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":22,\"outFeatures\":88}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 58-token sequences with 100 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2713\nComponents:\n - input (input) params={\"shape\":[1,58]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,58]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":45573,\"embeddingDim\":152}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":152,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":152,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":152,\"outFeatures\":100}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 432-token sequences with 74 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2714\nComponents:\n - input (input) params={\"shape\":[1,432]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,432]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":34509,\"embeddingDim\":224}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":224,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[224]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":224,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[224]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":224,\"outFeatures\":74}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 3218-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2716\nComponents:\n - input (input) params={\"shape\":[1,52]}\n - fc1 (linear) params={\"inFeatures\":52,\"outFeatures\":3218}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3218,\"outFeatures\":3218}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":3218,\"outFeatures\":42}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":52,\"outFeatures\":92}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":92,\"outFeatures\":92}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":92,\"outFeatures\":42}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 194-feature, 79-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2717\nComponents:\n - input (input) params={\"shape\":[1,194]}\n - fc1 (linear) params={\"inFeatures\":194,\"outFeatures\":39}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":39,\"outFeatures\":246}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":246,\"outFeatures\":79}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":39}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":246}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 221-feature user input and a 204-feature item input, each through its own 2-layer MLP tower ending at width 466, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2718\nComponents:\n - user_input (input) params={\"shape\":[1,221]}\n - item_input (input) params={\"shape\":[1,204]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,221]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,204]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":221,\"outFeatures\":466}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":466,\"outFeatures\":466}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":204,\"outFeatures\":466}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":466,\"outFeatures\":466}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":932,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (121-feature input, 18 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2719\nComponents:\n - input (input) params={\"shape\":[1,121]}\n - fc1 (linear) params={\"inFeatures\":121,\"outFeatures\":15}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":15,\"outFeatures\":15}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":15,\"outFeatures\":18}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":121,\"outFeatures\":843}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":843,\"outFeatures\":843}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":843,\"outFeatures\":18}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 444-feature input with 3 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2720\nComponents:\n - input (input) params={\"shape\":[1,444]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,444]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":444,\"outFeatures\":776}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":776,\"outFeatures\":376}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":376,\"outFeatures\":888}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":888,\"outFeatures\":94}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":94,\"outFeatures\":91}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":91,\"outFeatures\":3}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1305-dim input: encode down to a 45-dim bottleneck and decode back to 1305. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2721\nComponents:\n - input (input) params={\"shape\":[1,1305]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1305]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1305,\"outFeatures\":143}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":143,\"outFeatures\":45}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":45,\"outFeatures\":143}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":143,\"outFeatures\":1305}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x59x59 image with 86 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2722\nComponents:\n - input (input) params={\"shape\":[1,3,59,59]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,59,59]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":58,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":58,\"outChannels\":34,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":34,\"outFeatures\":86}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 135-token sequences with 97 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2723\nComponents:\n - input (input) params={\"shape\":[1,135]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,135]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":36714,\"embeddingDim\":244}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":244,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":244,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":244,\"outFeatures\":97}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 156-token sequences with 9 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2724\nComponents:\n - input (input) params={\"shape\":[1,156]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,156]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":38677,\"embeddingDim\":172}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":172,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[172]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":172,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[172]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":172,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[172]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":172,\"outFeatures\":9}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (378) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-2725\nComponents:\n - input (input) params={\"shape\":[1,185]}\n - embed (embedding) params={\"numEmbeddings\":17734,\"embeddingDim\":378}\n - attn (multiHeadAttention) params={\"embedDim\":378,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":378,\"outFeatures\":78}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 1962-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2726\nComponents:\n - input (input) params={\"shape\":[1,104]}\n - fc1 (linear) params={\"inFeatures\":104,\"outFeatures\":1962}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":1962,\"outFeatures\":1962}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":1962,\"outFeatures\":27}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":104,\"outFeatures\":364}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":364,\"outFeatures\":364}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":364,\"outFeatures\":27}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 57-feature, 55-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2727\nComponents:\n - input (input) params={\"shape\":[1,57]}\n - fc1 (linear) params={\"inFeatures\":57,\"outFeatures\":448}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":448,\"outFeatures\":503}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":503,\"outFeatures\":455}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":455,\"outFeatures\":326}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":326,\"outFeatures\":504}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":504,\"outFeatures\":55}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":448}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":503}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":455}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":326}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":504}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 208-feature user input and a 53-feature item input, each through its own 2-layer MLP tower ending at width 478, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2728\nComponents:\n - user_input (input) params={\"shape\":[1,208]}\n - item_input (input) params={\"shape\":[1,53]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,208]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,53]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":208,\"outFeatures\":478}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":478,\"outFeatures\":478}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":53,\"outFeatures\":478}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":478,\"outFeatures\":478}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":956,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (21-feature input, 27 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2729\nComponents:\n - input (input) params={\"shape\":[1,21]}\n - fc1 (linear) params={\"inFeatures\":21,\"outFeatures\":10}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":10,\"outFeatures\":10}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":10,\"outFeatures\":27}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":21,\"outFeatures\":1051}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1051,\"outFeatures\":1051}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1051,\"outFeatures\":27}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 23-feature input with 146 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2730\nComponents:\n - input (input) params={\"shape\":[1,23]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,23]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":23,\"outFeatures\":80}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":80,\"outFeatures\":705}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":705,\"outFeatures\":270}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":270,\"outFeatures\":776}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":776,\"outFeatures\":146}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1941-dim input: encode down to a 219-dim bottleneck and decode back to 1941. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2731\nComponents:\n - input (input) params={\"shape\":[1,1941]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1941]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1941,\"outFeatures\":378}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":378,\"outFeatures\":219}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":219,\"outFeatures\":378}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":378,\"outFeatures\":1941}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x46x46 image with 3 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2732\nComponents:\n - input (input) params={\"shape\":[1,3,46,46]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,46,46]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":44,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":44,\"outChannels\":20,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":20,\"outFeatures\":3}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 43-token sequences with 54 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2733\nComponents:\n - input (input) params={\"shape\":[1,43]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,43]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":22244,\"embeddingDim\":74}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":74,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":74,\"outFeatures\":54}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 390-token sequences with 3 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2734\nComponents:\n - input (input) params={\"shape\":[1,390]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,390]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":34581,\"embeddingDim\":160}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":160,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[160]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":160,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[160]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":160,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[160]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":160,\"outFeatures\":3}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3194-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2736\nComponents:\n - input (input) params={\"shape\":[1,225]}\n - fc1 (linear) params={\"inFeatures\":225,\"outFeatures\":3194}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3194,\"outFeatures\":3194}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3194,\"outFeatures\":3194}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3194,\"outFeatures\":3194}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3194,\"outFeatures\":11}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":225,\"outFeatures\":311}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":311,\"outFeatures\":311}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":311,\"outFeatures\":311}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":311,\"outFeatures\":311}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":311,\"outFeatures\":11}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 185-feature, 45-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2737\nComponents:\n - input (input) params={\"shape\":[1,185]}\n - fc1 (linear) params={\"inFeatures\":185,\"outFeatures\":289}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":289,\"outFeatures\":249}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":249,\"outFeatures\":45}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":289}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":249}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 38-feature user input and a 178-feature item input, each through its own 2-layer MLP tower ending at width 42, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2738\nComponents:\n - user_input (input) params={\"shape\":[1,38]}\n - item_input (input) params={\"shape\":[1,178]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,38]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,178]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":38,\"outFeatures\":42}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":42,\"outFeatures\":42}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":178,\"outFeatures\":42}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":42,\"outFeatures\":42}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":84,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (87-feature input, 26 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2739\nComponents:\n - input (input) params={\"shape\":[1,87]}\n - fc1 (linear) params={\"inFeatures\":87,\"outFeatures\":12}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":12,\"outFeatures\":12}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":12,\"outFeatures\":26}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":87,\"outFeatures\":944}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":944,\"outFeatures\":944}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":944,\"outFeatures\":26}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 451-feature input with 174 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2740\nComponents:\n - input (input) params={\"shape\":[1,451]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,451]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":451,\"outFeatures\":694}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":694,\"outFeatures\":193}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":193,\"outFeatures\":375}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":375,\"outFeatures\":48}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":48,\"outFeatures\":174}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 842-dim input: encode down to a 124-dim bottleneck and decode back to 842. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2741\nComponents:\n - input (input) params={\"shape\":[1,842]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,842]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":842,\"outFeatures\":561}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":561,\"outFeatures\":124}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":124,\"outFeatures\":561}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":561,\"outFeatures\":842}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x29x29 image with 55 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2742\nComponents:\n - input (input) params={\"shape\":[1,3,29,29]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,29,29]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":60,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":60,\"outChannels\":14,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":14,\"outFeatures\":55}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 440-token sequences with 96 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2743\nComponents:\n - input (input) params={\"shape\":[1,440]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,440]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":32243,\"embeddingDim\":240}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":240,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":240,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":240,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":240,\"outFeatures\":96}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 423-token sequences with 37 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2744\nComponents:\n - input (input) params={\"shape\":[1,423]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,423]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":10618,\"embeddingDim\":344}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":344,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[344]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":344,\"outFeatures\":37}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3116-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2746\nComponents:\n - input (input) params={\"shape\":[1,152]}\n - fc1 (linear) params={\"inFeatures\":152,\"outFeatures\":3116}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3116,\"outFeatures\":3116}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3116,\"outFeatures\":3116}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3116,\"outFeatures\":3116}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3116,\"outFeatures\":42}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":152,\"outFeatures\":226}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":226,\"outFeatures\":226}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":226,\"outFeatures\":226}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":226,\"outFeatures\":226}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":226,\"outFeatures\":42}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 73-feature, 67-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2747\nComponents:\n - input (input) params={\"shape\":[1,73]}\n - fc1 (linear) params={\"inFeatures\":73,\"outFeatures\":494}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":494,\"outFeatures\":508}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":508,\"outFeatures\":196}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":196,\"outFeatures\":67}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":494}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":508}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":196}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 111-feature user input and a 172-feature item input, each through its own 2-layer MLP tower ending at width 55, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2748\nComponents:\n - user_input (input) params={\"shape\":[1,111]}\n - item_input (input) params={\"shape\":[1,172]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,111]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,172]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":111,\"outFeatures\":55}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":55,\"outFeatures\":55}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":172,\"outFeatures\":55}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":55,\"outFeatures\":55}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":110,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (117-feature input, 20 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2749\nComponents:\n - input (input) params={\"shape\":[1,117]}\n - fc1 (linear) params={\"inFeatures\":117,\"outFeatures\":17}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":17,\"outFeatures\":17}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":17,\"outFeatures\":20}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":117,\"outFeatures\":900}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":900,\"outFeatures\":900}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":900,\"outFeatures\":20}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 484-feature input with 51 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2750\nComponents:\n - input (input) params={\"shape\":[1,484]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,484]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":484,\"outFeatures\":831}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":831,\"outFeatures\":858}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":858,\"outFeatures\":51}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 247-dim input: encode down to a 51-dim bottleneck and decode back to 247. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2751\nComponents:\n - input (input) params={\"shape\":[1,247]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,247]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":247,\"outFeatures\":153}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":153,\"outFeatures\":51}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":51,\"outFeatures\":153}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":153,\"outFeatures\":247}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x51x51 image with 96 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2752\nComponents:\n - input (input) params={\"shape\":[1,3,51,51]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,51,51]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":53,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":53,\"outChannels\":23,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":23,\"outChannels\":38,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":38,\"outChannels\":16,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":16,\"outFeatures\":96}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 395-token sequences with 63 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2753\nComponents:\n - input (input) params={\"shape\":[1,395]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,395]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":44371,\"embeddingDim\":224}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":224,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":224,\"outFeatures\":63}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 382-token sequences with 18 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2754\nComponents:\n - input (input) params={\"shape\":[1,382]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,382]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":25957,\"embeddingDim\":304}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":304,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[304]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":304,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[304]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":304,\"outFeatures\":18}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3079-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2756\nComponents:\n - input (input) params={\"shape\":[1,212]}\n - fc1 (linear) params={\"inFeatures\":212,\"outFeatures\":3079}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3079,\"outFeatures\":3079}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3079,\"outFeatures\":3079}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3079,\"outFeatures\":3079}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3079,\"outFeatures\":48}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":212,\"outFeatures\":380}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":380,\"outFeatures\":380}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":380,\"outFeatures\":380}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":380,\"outFeatures\":380}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":380,\"outFeatures\":48}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 176-feature, 18-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2757\nComponents:\n - input (input) params={\"shape\":[1,176]}\n - fc1 (linear) params={\"inFeatures\":176,\"outFeatures\":282}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":282,\"outFeatures\":181}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":181,\"outFeatures\":86}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":86,\"outFeatures\":18}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":282}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":181}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":86}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 148-feature user input and a 92-feature item input, each through its own 2-layer MLP tower ending at width 80, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2758\nComponents:\n - user_input (input) params={\"shape\":[1,148]}\n - item_input (input) params={\"shape\":[1,92]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,148]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,92]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":148,\"outFeatures\":80}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":80,\"outFeatures\":80}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":92,\"outFeatures\":80}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":80,\"outFeatures\":80}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":160,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (82-feature input, 31 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2759\nComponents:\n - input (input) params={\"shape\":[1,82]}\n - fc1 (linear) params={\"inFeatures\":82,\"outFeatures\":11}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":11,\"outFeatures\":11}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":11,\"outFeatures\":31}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":82,\"outFeatures\":1318}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1318,\"outFeatures\":1318}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1318,\"outFeatures\":31}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 74-feature input with 77 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2760\nComponents:\n - input (input) params={\"shape\":[1,74]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,74]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":74,\"outFeatures\":982}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":982,\"outFeatures\":91}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":91,\"outFeatures\":141}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":141,\"outFeatures\":301}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":301,\"outFeatures\":531}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":531,\"outFeatures\":808}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":808,\"outFeatures\":77}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 2033-dim input: encode down to a 126-dim bottleneck and decode back to 2033. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2761\nComponents:\n - input (input) params={\"shape\":[1,2033]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,2033]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":2033,\"outFeatures\":885}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":885,\"outFeatures\":126}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":126,\"outFeatures\":885}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":885,\"outFeatures\":2033}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x54x54 image with 11 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2762\nComponents:\n - input (input) params={\"shape\":[1,3,54,54]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,54,54]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":23,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":23,\"outChannels\":61,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":61,\"outChannels\":40,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":40,\"outChannels\":23,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":23,\"outFeatures\":11}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 399-token sequences with 7 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2763\nComponents:\n - input (input) params={\"shape\":[1,399]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,399]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":17511,\"embeddingDim\":64}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":64,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":64,\"outFeatures\":7}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 205-token sequences with 72 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2764\nComponents:\n - input (input) params={\"shape\":[1,205]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,205]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":32184,\"embeddingDim\":528}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":528,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[528]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":528,\"outFeatures\":72}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 2525-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2766\nComponents:\n - input (input) params={\"shape\":[1,249]}\n - fc1 (linear) params={\"inFeatures\":249,\"outFeatures\":2525}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2525,\"outFeatures\":2525}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2525,\"outFeatures\":2525}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":2525,\"outFeatures\":49}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":249,\"outFeatures\":311}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":311,\"outFeatures\":311}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":311,\"outFeatures\":311}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":311,\"outFeatures\":49}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 80-feature, 7-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2767\nComponents:\n - input (input) params={\"shape\":[1,80]}\n - fc1 (linear) params={\"inFeatures\":80,\"outFeatures\":439}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":439,\"outFeatures\":185}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":185,\"outFeatures\":292}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":292,\"outFeatures\":302}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":302,\"outFeatures\":7}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":439}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":185}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":292}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":302}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 24-feature user input and a 252-feature item input, each through its own 2-layer MLP tower ending at width 491, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2768\nComponents:\n - user_input (input) params={\"shape\":[1,24]}\n - item_input (input) params={\"shape\":[1,252]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,24]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,252]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":24,\"outFeatures\":491}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":491,\"outFeatures\":491}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":252,\"outFeatures\":491}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":491,\"outFeatures\":491}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":982,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (36-feature input, 4 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2769\nComponents:\n - input (input) params={\"shape\":[1,36]}\n - fc1 (linear) params={\"inFeatures\":36,\"outFeatures\":24}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":24,\"outFeatures\":24}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":24,\"outFeatures\":4}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":36,\"outFeatures\":1108}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1108,\"outFeatures\":1108}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1108,\"outFeatures\":4}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 347-feature input with 85 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2770\nComponents:\n - input (input) params={\"shape\":[1,347]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,347]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":347,\"outFeatures\":524}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":524,\"outFeatures\":217}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":217,\"outFeatures\":1001}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":1001,\"outFeatures\":85}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 251-dim input: encode down to a 209-dim bottleneck and decode back to 251. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2771\nComponents:\n - input (input) params={\"shape\":[1,251]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,251]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":251,\"outFeatures\":572}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":572,\"outFeatures\":209}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":209,\"outFeatures\":572}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":572,\"outFeatures\":251}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x55x55 image with 54 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2772\nComponents:\n - input (input) params={\"shape\":[1,3,55,55]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,55,55]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":15,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":15,\"outChannels\":8,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":8,\"outFeatures\":54}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 162-token sequences with 94 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2773\nComponents:\n - input (input) params={\"shape\":[1,162]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,162]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":27349,\"embeddingDim\":368}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":368,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":368,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":368,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":368,\"outFeatures\":94}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 435-token sequences with 43 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2774\nComponents:\n - input (input) params={\"shape\":[1,435]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,435]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":19579,\"embeddingDim\":320}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":320,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[320]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":320,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[320]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":320,\"outFeatures\":43}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (142) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-2775\nComponents:\n - input (input) params={\"shape\":[1,271]}\n - embed (embedding) params={\"numEmbeddings\":35933,\"embeddingDim\":142}\n - attn (multiHeadAttention) params={\"embedDim\":142,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":142,\"outFeatures\":54}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 2967-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2776\nComponents:\n - input (input) params={\"shape\":[1,82]}\n - fc1 (linear) params={\"inFeatures\":82,\"outFeatures\":2967}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2967,\"outFeatures\":2967}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":2967,\"outFeatures\":38}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":82,\"outFeatures\":165}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":165,\"outFeatures\":165}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":165,\"outFeatures\":38}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 240-feature, 30-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2777\nComponents:\n - input (input) params={\"shape\":[1,240]}\n - fc1 (linear) params={\"inFeatures\":240,\"outFeatures\":368}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":368,\"outFeatures\":105}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":105,\"outFeatures\":251}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":251,\"outFeatures\":30}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":368}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":105}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":251}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 155-feature user input and a 217-feature item input, each through its own 2-layer MLP tower ending at width 271, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2778\nComponents:\n - user_input (input) params={\"shape\":[1,155]}\n - item_input (input) params={\"shape\":[1,217]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,155]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,217]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":155,\"outFeatures\":271}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":271,\"outFeatures\":271}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":217,\"outFeatures\":271}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":271,\"outFeatures\":271}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":542,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (128-feature input, 26 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2779\nComponents:\n - input (input) params={\"shape\":[1,128]}\n - fc1 (linear) params={\"inFeatures\":128,\"outFeatures\":7}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":7,\"outFeatures\":7}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":7,\"outFeatures\":26}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":128,\"outFeatures\":1112}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1112,\"outFeatures\":1112}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1112,\"outFeatures\":26}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 291-feature input with 72 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2780\nComponents:\n - input (input) params={\"shape\":[1,291]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,291]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":291,\"outFeatures\":212}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":212,\"outFeatures\":1014}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":1014,\"outFeatures\":921}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":921,\"outFeatures\":72}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1462-dim input: encode down to a 25-dim bottleneck and decode back to 1462. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2781\nComponents:\n - input (input) params={\"shape\":[1,1462]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1462]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1462,\"outFeatures\":743}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":743,\"outFeatures\":25}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":25,\"outFeatures\":743}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":743,\"outFeatures\":1462}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x64x64 image with 28 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2782\nComponents:\n - input (input) params={\"shape\":[1,3,64,64]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,64,64]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":50,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":50,\"outChannels\":31,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":31,\"outChannels\":55,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":55,\"outChannels\":47,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":47,\"outFeatures\":28}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 402-token sequences with 20 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2783\nComponents:\n - input (input) params={\"shape\":[1,402]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,402]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":48940,\"embeddingDim\":60}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":60,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":60,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":60,\"outFeatures\":20}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 452-token sequences with 53 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2784\nComponents:\n - input (input) params={\"shape\":[1,452]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,452]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":21003,\"embeddingDim\":704}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":704,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[704]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":704,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[704]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":704,\"outFeatures\":53}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 2267-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2786\nComponents:\n - input (input) params={\"shape\":[1,54]}\n - fc1 (linear) params={\"inFeatures\":54,\"outFeatures\":2267}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2267,\"outFeatures\":2267}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2267,\"outFeatures\":2267}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":2267,\"outFeatures\":2267}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":2267,\"outFeatures\":12}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":54,\"outFeatures\":360}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":360,\"outFeatures\":360}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":360,\"outFeatures\":360}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":360,\"outFeatures\":360}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":360,\"outFeatures\":12}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 230-feature, 57-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2787\nComponents:\n - input (input) params={\"shape\":[1,230]}\n - fc1 (linear) params={\"inFeatures\":230,\"outFeatures\":389}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":389,\"outFeatures\":84}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":84,\"outFeatures\":247}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":247,\"outFeatures\":57}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":389}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":84}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":247}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 53-feature user input and a 26-feature item input, each through its own 2-layer MLP tower ending at width 148, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2788\nComponents:\n - user_input (input) params={\"shape\":[1,53]}\n - item_input (input) params={\"shape\":[1,26]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,53]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,26]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":53,\"outFeatures\":148}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":148,\"outFeatures\":148}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":26,\"outFeatures\":148}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":148,\"outFeatures\":148}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":296,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (27-feature input, 19 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2789\nComponents:\n - input (input) params={\"shape\":[1,27]}\n - fc1 (linear) params={\"inFeatures\":27,\"outFeatures\":13}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":13,\"outFeatures\":13}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":13,\"outFeatures\":19}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":27,\"outFeatures\":1059}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1059,\"outFeatures\":1059}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1059,\"outFeatures\":19}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 39-feature input with 104 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2790\nComponents:\n - input (input) params={\"shape\":[1,39]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,39]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":39,\"outFeatures\":960}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":960,\"outFeatures\":455}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":455,\"outFeatures\":104}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1120-dim input: encode down to a 181-dim bottleneck and decode back to 1120. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2791\nComponents:\n - input (input) params={\"shape\":[1,1120]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1120]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1120,\"outFeatures\":311}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":311,\"outFeatures\":181}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":181,\"outFeatures\":311}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":311,\"outFeatures\":1120}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x37x37 image with 99 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2792\nComponents:\n - input (input) params={\"shape\":[1,3,37,37]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,37,37]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":17,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":17,\"outChannels\":36,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":36,\"outFeatures\":99}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 442-token sequences with 70 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2793\nComponents:\n - input (input) params={\"shape\":[1,442]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,442]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":16553,\"embeddingDim\":220}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":220,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":220,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":220,\"outFeatures\":70}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 211-token sequences with 91 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2794\nComponents:\n - input (input) params={\"shape\":[1,211]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,211]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":13060,\"embeddingDim\":304}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":304,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[304]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":304,\"outFeatures\":91}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 2385-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2796\nComponents:\n - input (input) params={\"shape\":[1,35]}\n - fc1 (linear) params={\"inFeatures\":35,\"outFeatures\":2385}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2385,\"outFeatures\":2385}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":2385,\"outFeatures\":45}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":35,\"outFeatures\":328}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":328,\"outFeatures\":328}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":328,\"outFeatures\":45}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 153-feature, 67-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2797\nComponents:\n - input (input) params={\"shape\":[1,153]}\n - fc1 (linear) params={\"inFeatures\":153,\"outFeatures\":406}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":406,\"outFeatures\":320}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":320,\"outFeatures\":231}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":231,\"outFeatures\":67}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":406}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":320}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":231}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 159-feature user input and a 118-feature item input, each through its own 2-layer MLP tower ending at width 511, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2798\nComponents:\n - user_input (input) params={\"shape\":[1,159]}\n - item_input (input) params={\"shape\":[1,118]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,159]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,118]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":159,\"outFeatures\":511}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":511,\"outFeatures\":511}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":118,\"outFeatures\":511}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":511,\"outFeatures\":511}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":1022,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (53-feature input, 11 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2799\nComponents:\n - input (input) params={\"shape\":[1,53]}\n - fc1 (linear) params={\"inFeatures\":53,\"outFeatures\":15}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":15,\"outFeatures\":15}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":15,\"outFeatures\":11}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":53,\"outFeatures\":915}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":915,\"outFeatures\":915}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":915,\"outFeatures\":11}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 224-feature input with 140 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2800\nComponents:\n - input (input) params={\"shape\":[1,224]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,224]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":224,\"outFeatures\":91}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":91,\"outFeatures\":996}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":996,\"outFeatures\":140}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 484-dim input: encode down to a 135-dim bottleneck and decode back to 484. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2801\nComponents:\n - input (input) params={\"shape\":[1,484]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,484]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":484,\"outFeatures\":413}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":413,\"outFeatures\":135}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":135,\"outFeatures\":413}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":413,\"outFeatures\":484}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x25x25 image with 75 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2802\nComponents:\n - input (input) params={\"shape\":[1,3,25,25]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,25,25]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":47,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":47,\"outChannels\":55,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":55,\"outChannels\":45,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":45,\"outChannels\":35,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":35,\"outFeatures\":75}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 473-token sequences with 28 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2803\nComponents:\n - input (input) params={\"shape\":[1,473]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,473]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":8161,\"embeddingDim\":90}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":90,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":90,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":90,\"outFeatures\":28}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 385-token sequences with 90 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2804\nComponents:\n - input (input) params={\"shape\":[1,385]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,385]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":18896,\"embeddingDim\":224}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":224,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[224]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":224,\"outFeatures\":90}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 1842-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2806\nComponents:\n - input (input) params={\"shape\":[1,125]}\n - fc1 (linear) params={\"inFeatures\":125,\"outFeatures\":1842}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":1842,\"outFeatures\":1842}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":1842,\"outFeatures\":1842}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":1842,\"outFeatures\":12}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":125,\"outFeatures\":92}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":92,\"outFeatures\":92}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":92,\"outFeatures\":92}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":92,\"outFeatures\":12}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 155-feature, 48-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2807\nComponents:\n - input (input) params={\"shape\":[1,155]}\n - fc1 (linear) params={\"inFeatures\":155,\"outFeatures\":304}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":304,\"outFeatures\":299}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":299,\"outFeatures\":320}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":320,\"outFeatures\":48}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":304}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":299}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":320}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 200-feature user input and a 50-feature item input, each through its own 2-layer MLP tower ending at width 131, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2808\nComponents:\n - user_input (input) params={\"shape\":[1,200]}\n - item_input (input) params={\"shape\":[1,50]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,200]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,50]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":200,\"outFeatures\":131}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":131,\"outFeatures\":131}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":50,\"outFeatures\":131}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":131,\"outFeatures\":131}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":262,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (104-feature input, 2 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2809\nComponents:\n - input (input) params={\"shape\":[1,104]}\n - fc1 (linear) params={\"inFeatures\":104,\"outFeatures\":5}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":5,\"outFeatures\":5}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":5,\"outFeatures\":2}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":104,\"outFeatures\":723}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":723,\"outFeatures\":723}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":723,\"outFeatures\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 455-feature input with 144 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2810\nComponents:\n - input (input) params={\"shape\":[1,455]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,455]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":455,\"outFeatures\":196}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":196,\"outFeatures\":699}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":699,\"outFeatures\":204}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":204,\"outFeatures\":136}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":136,\"outFeatures\":144}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 107-dim input: encode down to a 143-dim bottleneck and decode back to 107. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2811\nComponents:\n - input (input) params={\"shape\":[1,107]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,107]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":107,\"outFeatures\":1017}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":1017,\"outFeatures\":143}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":143,\"outFeatures\":1017}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":1017,\"outFeatures\":107}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x44x44 image with 88 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2812\nComponents:\n - input (input) params={\"shape\":[1,3,44,44]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,44,44]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":32,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":32,\"outChannels\":39,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":39,\"outChannels\":35,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":35,\"outChannels\":52,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":52,\"outFeatures\":88}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 87-token sequences with 17 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2813\nComponents:\n - input (input) params={\"shape\":[1,87]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,87]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":37152,\"embeddingDim\":232}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":232,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":232,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":232,\"outFeatures\":17}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 339-token sequences with 99 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2814\nComponents:\n - input (input) params={\"shape\":[1,339]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,339]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":48905,\"embeddingDim\":304}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":304,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[304]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":304,\"outFeatures\":99}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (452) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-2815\nComponents:\n - input (input) params={\"shape\":[1,137]}\n - embed (embedding) params={\"numEmbeddings\":23125,\"embeddingDim\":452}\n - attn (multiHeadAttention) params={\"embedDim\":452,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":452,\"outFeatures\":81}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":4}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 2639-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2816\nComponents:\n - input (input) params={\"shape\":[1,236]}\n - fc1 (linear) params={\"inFeatures\":236,\"outFeatures\":2639}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2639,\"outFeatures\":2639}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2639,\"outFeatures\":2639}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":2639,\"outFeatures\":2639}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":2639,\"outFeatures\":37}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":236,\"outFeatures\":160}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":160,\"outFeatures\":160}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":160,\"outFeatures\":160}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":160,\"outFeatures\":160}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":160,\"outFeatures\":37}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 238-feature, 74-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2817\nComponents:\n - input (input) params={\"shape\":[1,238]}\n - fc1 (linear) params={\"inFeatures\":238,\"outFeatures\":191}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":191,\"outFeatures\":241}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":241,\"outFeatures\":200}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":200,\"outFeatures\":74}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":191}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":241}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":200}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 66-feature user input and a 180-feature item input, each through its own 2-layer MLP tower ending at width 75, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2818\nComponents:\n - user_input (input) params={\"shape\":[1,66]}\n - item_input (input) params={\"shape\":[1,180]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,66]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,180]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":66,\"outFeatures\":75}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":75,\"outFeatures\":75}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":180,\"outFeatures\":75}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":75,\"outFeatures\":75}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":150,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (50-feature input, 21 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2819\nComponents:\n - input (input) params={\"shape\":[1,50]}\n - fc1 (linear) params={\"inFeatures\":50,\"outFeatures\":16}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":16,\"outFeatures\":16}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":16,\"outFeatures\":21}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":50,\"outFeatures\":1083}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1083,\"outFeatures\":1083}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1083,\"outFeatures\":21}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 511-feature input with 185 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2820\nComponents:\n - input (input) params={\"shape\":[1,511]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,511]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":511,\"outFeatures\":337}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":337,\"outFeatures\":888}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":888,\"outFeatures\":185}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 2033-dim input: encode down to a 164-dim bottleneck and decode back to 2033. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2821\nComponents:\n - input (input) params={\"shape\":[1,2033]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,2033]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":2033,\"outFeatures\":175}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":175,\"outFeatures\":164}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":164,\"outFeatures\":175}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":175,\"outFeatures\":2033}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x55x55 image with 8 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2822\nComponents:\n - input (input) params={\"shape\":[1,3,55,55]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,55,55]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":48,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":48,\"outChannels\":18,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":18,\"outChannels\":29,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":29,\"outFeatures\":8}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 330-token sequences with 2 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2823\nComponents:\n - input (input) params={\"shape\":[1,330]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,330]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":40609,\"embeddingDim\":106}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":106,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":106,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":106,\"outFeatures\":2}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 123-token sequences with 15 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2824\nComponents:\n - input (input) params={\"shape\":[1,123]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,123]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":12086,\"embeddingDim\":688}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":688,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[688]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":688,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[688]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":688,\"outFeatures\":15}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3956-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2826\nComponents:\n - input (input) params={\"shape\":[1,246]}\n - fc1 (linear) params={\"inFeatures\":246,\"outFeatures\":3956}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3956,\"outFeatures\":3956}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3956,\"outFeatures\":3956}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3956,\"outFeatures\":3956}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3956,\"outFeatures\":32}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":246,\"outFeatures\":254}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":254,\"outFeatures\":254}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":254,\"outFeatures\":254}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":254,\"outFeatures\":254}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":254,\"outFeatures\":32}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 33-feature, 44-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2827\nComponents:\n - input (input) params={\"shape\":[1,33]}\n - fc1 (linear) params={\"inFeatures\":33,\"outFeatures\":326}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":326,\"outFeatures\":223}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":223,\"outFeatures\":453}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":453,\"outFeatures\":234}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":234,\"outFeatures\":103}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":103,\"outFeatures\":44}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":326}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":223}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":453}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":234}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":103}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 124-feature user input and a 109-feature item input, each through its own 2-layer MLP tower ending at width 409, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2828\nComponents:\n - user_input (input) params={\"shape\":[1,124]}\n - item_input (input) params={\"shape\":[1,109]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,124]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,109]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":124,\"outFeatures\":409}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":409,\"outFeatures\":409}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":109,\"outFeatures\":409}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":409,\"outFeatures\":409}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":818,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (50-feature input, 39 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2829\nComponents:\n - input (input) params={\"shape\":[1,50]}\n - fc1 (linear) params={\"inFeatures\":50,\"outFeatures\":7}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":7,\"outFeatures\":7}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":7,\"outFeatures\":39}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":50,\"outFeatures\":1171}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1171,\"outFeatures\":1171}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1171,\"outFeatures\":39}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 355-feature input with 54 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2830\nComponents:\n - input (input) params={\"shape\":[1,355]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,355]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":355,\"outFeatures\":213}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":213,\"outFeatures\":178}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":178,\"outFeatures\":54}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1477-dim input: encode down to a 175-dim bottleneck and decode back to 1477. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2831\nComponents:\n - input (input) params={\"shape\":[1,1477]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1477]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1477,\"outFeatures\":156}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":156,\"outFeatures\":175}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":175,\"outFeatures\":156}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":156,\"outFeatures\":1477}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x64x64 image with 9 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2832\nComponents:\n - input (input) params={\"shape\":[1,3,64,64]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,64,64]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":53,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":53,\"outChannels\":41,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":41,\"outChannels\":55,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":55,\"outFeatures\":9}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 125-token sequences with 7 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2833\nComponents:\n - input (input) params={\"shape\":[1,125]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,125]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":27573,\"embeddingDim\":240}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":240,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":240,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":240,\"outFeatures\":7}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 472-token sequences with 25 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2834\nComponents:\n - input (input) params={\"shape\":[1,472]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,472]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":8069,\"embeddingDim\":304}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":304,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[304]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":304,\"outFeatures\":25}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (342) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-2835\nComponents:\n - input (input) params={\"shape\":[1,247]}\n - embed (embedding) params={\"numEmbeddings\":46219,\"embeddingDim\":342}\n - attn (multiHeadAttention) params={\"embedDim\":342,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":342,\"outFeatures\":4}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 3072-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2836\nComponents:\n - input (input) params={\"shape\":[1,230]}\n - fc1 (linear) params={\"inFeatures\":230,\"outFeatures\":3072}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3072,\"outFeatures\":3072}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3072,\"outFeatures\":3072}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":3072,\"outFeatures\":22}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":230,\"outFeatures\":126}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":126,\"outFeatures\":126}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":126,\"outFeatures\":126}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":126,\"outFeatures\":22}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 207-feature, 74-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2837\nComponents:\n - input (input) params={\"shape\":[1,207]}\n - fc1 (linear) params={\"inFeatures\":207,\"outFeatures\":467}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":467,\"outFeatures\":90}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":90,\"outFeatures\":39}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":39,\"outFeatures\":402}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":402,\"outFeatures\":92}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":92,\"outFeatures\":74}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":467}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":90}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":39}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":402}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":92}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 228-feature user input and a 150-feature item input, each through its own 2-layer MLP tower ending at width 339, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2838\nComponents:\n - user_input (input) params={\"shape\":[1,228]}\n - item_input (input) params={\"shape\":[1,150]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,228]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,150]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":228,\"outFeatures\":339}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":339,\"outFeatures\":339}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":150,\"outFeatures\":339}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":339,\"outFeatures\":339}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":678,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (106-feature input, 50 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2839\nComponents:\n - input (input) params={\"shape\":[1,106]}\n - fc1 (linear) params={\"inFeatures\":106,\"outFeatures\":9}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":9,\"outFeatures\":9}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":9,\"outFeatures\":50}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":106,\"outFeatures\":752}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":752,\"outFeatures\":752}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":752,\"outFeatures\":50}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 451-feature input with 145 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2840\nComponents:\n - input (input) params={\"shape\":[1,451]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,451]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":451,\"outFeatures\":674}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":674,\"outFeatures\":615}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":615,\"outFeatures\":516}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":516,\"outFeatures\":901}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":901,\"outFeatures\":145}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 672-dim input: encode down to a 62-dim bottleneck and decode back to 672. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2841\nComponents:\n - input (input) params={\"shape\":[1,672]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,672]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":672,\"outFeatures\":875}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":875,\"outFeatures\":62}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":62,\"outFeatures\":875}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":875,\"outFeatures\":672}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x59x59 image with 70 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2842\nComponents:\n - input (input) params={\"shape\":[1,3,59,59]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,59,59]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":26,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":26,\"outChannels\":61,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":61,\"outChannels\":57,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":57,\"outChannels\":18,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":18,\"outFeatures\":70}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 107-token sequences with 13 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2843\nComponents:\n - input (input) params={\"shape\":[1,107]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,107]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":41504,\"embeddingDim\":216}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":216,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":216,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":216,\"outFeatures\":13}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 286-token sequences with 22 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2844\nComponents:\n - input (input) params={\"shape\":[1,286]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,286]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":47998,\"embeddingDim\":128}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":128,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[128]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":128,\"outFeatures\":22}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (90) is not divisible by numHeads (7). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-2845\nComponents:\n - input (input) params={\"shape\":[1,217]}\n - embed (embedding) params={\"numEmbeddings\":38994,\"embeddingDim\":90}\n - attn (multiHeadAttention) params={\"embedDim\":90,\"numHeads\":7}\n - head (linear) params={\"inFeatures\":90,\"outFeatures\":99}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3814-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2846\nComponents:\n - input (input) params={\"shape\":[1,221]}\n - fc1 (linear) params={\"inFeatures\":221,\"outFeatures\":3814}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3814,\"outFeatures\":3814}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3814,\"outFeatures\":3814}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3814,\"outFeatures\":3814}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3814,\"outFeatures\":44}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":221,\"outFeatures\":207}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":207,\"outFeatures\":207}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":207,\"outFeatures\":207}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":207,\"outFeatures\":207}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":207,\"outFeatures\":44}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 16-feature, 42-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2847\nComponents:\n - input (input) params={\"shape\":[1,16]}\n - fc1 (linear) params={\"inFeatures\":16,\"outFeatures\":118}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":118,\"outFeatures\":265}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":265,\"outFeatures\":53}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":53,\"outFeatures\":42}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":118}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":265}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":53}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 182-feature user input and a 131-feature item input, each through its own 2-layer MLP tower ending at width 37, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2848\nComponents:\n - user_input (input) params={\"shape\":[1,182]}\n - item_input (input) params={\"shape\":[1,131]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,182]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,131]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":182,\"outFeatures\":37}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":37,\"outFeatures\":37}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":131,\"outFeatures\":37}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":37,\"outFeatures\":37}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":74,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (37-feature input, 18 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2849\nComponents:\n - input (input) params={\"shape\":[1,37]}\n - fc1 (linear) params={\"inFeatures\":37,\"outFeatures\":16}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":16,\"outFeatures\":16}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":16,\"outFeatures\":18}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":37,\"outFeatures\":1228}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1228,\"outFeatures\":1228}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1228,\"outFeatures\":18}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 178-feature input with 182 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2850\nComponents:\n - input (input) params={\"shape\":[1,178]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,178]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":178,\"outFeatures\":510}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":510,\"outFeatures\":839}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":839,\"outFeatures\":23}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":23,\"outFeatures\":654}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":654,\"outFeatures\":1003}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":1003,\"outFeatures\":182}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1070-dim input: encode down to a 201-dim bottleneck and decode back to 1070. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2851\nComponents:\n - input (input) params={\"shape\":[1,1070]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1070]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1070,\"outFeatures\":341}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":341,\"outFeatures\":201}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":201,\"outFeatures\":341}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":341,\"outFeatures\":1070}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x34x34 image with 42 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2852\nComponents:\n - input (input) params={\"shape\":[1,3,34,34]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,34,34]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":54,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":54,\"outChannels\":15,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":15,\"outChannels\":56,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":56,\"outChannels\":22,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":22,\"outFeatures\":42}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 365-token sequences with 17 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2853\nComponents:\n - input (input) params={\"shape\":[1,365]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,365]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":12685,\"embeddingDim\":110}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":110,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":110,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":110,\"outFeatures\":17}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 375-token sequences with 26 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2854\nComponents:\n - input (input) params={\"shape\":[1,375]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,375]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":18538,\"embeddingDim\":176}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":176,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[176]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":176,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[176]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":176,\"outFeatures\":26}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 2578-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2856\nComponents:\n - input (input) params={\"shape\":[1,208]}\n - fc1 (linear) params={\"inFeatures\":208,\"outFeatures\":2578}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2578,\"outFeatures\":2578}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":2578,\"outFeatures\":13}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":208,\"outFeatures\":246}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":246,\"outFeatures\":246}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":246,\"outFeatures\":13}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 68-feature, 2-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2857\nComponents:\n - input (input) params={\"shape\":[1,68]}\n - fc1 (linear) params={\"inFeatures\":68,\"outFeatures\":293}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":293,\"outFeatures\":187}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":187,\"outFeatures\":80}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":80,\"outFeatures\":2}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":293}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":187}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":80}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 219-feature user input and a 32-feature item input, each through its own 2-layer MLP tower ending at width 354, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2858\nComponents:\n - user_input (input) params={\"shape\":[1,219]}\n - item_input (input) params={\"shape\":[1,32]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,219]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,32]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":219,\"outFeatures\":354}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":354,\"outFeatures\":354}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":32,\"outFeatures\":354}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":354,\"outFeatures\":354}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":708,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (65-feature input, 33 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2859\nComponents:\n - input (input) params={\"shape\":[1,65]}\n - fc1 (linear) params={\"inFeatures\":65,\"outFeatures\":19}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":19,\"outFeatures\":19}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":19,\"outFeatures\":33}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":65,\"outFeatures\":1086}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1086,\"outFeatures\":1086}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1086,\"outFeatures\":33}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 225-feature input with 22 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2860\nComponents:\n - input (input) params={\"shape\":[1,225]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,225]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":225,\"outFeatures\":708}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":708,\"outFeatures\":447}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":447,\"outFeatures\":735}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":735,\"outFeatures\":961}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":961,\"outFeatures\":22}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1508-dim input: encode down to a 24-dim bottleneck and decode back to 1508. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2861\nComponents:\n - input (input) params={\"shape\":[1,1508]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1508]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1508,\"outFeatures\":949}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":949,\"outFeatures\":24}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":24,\"outFeatures\":949}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":949,\"outFeatures\":1508}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x35x35 image with 64 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2862\nComponents:\n - input (input) params={\"shape\":[1,3,35,35]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,35,35]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":57,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":57,\"outChannels\":49,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":49,\"outChannels\":47,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":47,\"outChannels\":19,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":19,\"outFeatures\":64}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 110-token sequences with 99 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2863\nComponents:\n - input (input) params={\"shape\":[1,110]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,110]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":42353,\"embeddingDim\":152}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":152,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":152,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":152,\"outFeatures\":99}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 457-token sequences with 53 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2864\nComponents:\n - input (input) params={\"shape\":[1,457]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,457]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":45466,\"embeddingDim\":80}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":80,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[80]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":80,\"outFeatures\":53}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (434) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-2865\nComponents:\n - input (input) params={\"shape\":[1,147]}\n - embed (embedding) params={\"numEmbeddings\":11760,\"embeddingDim\":434}\n - attn (multiHeadAttention) params={\"embedDim\":434,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":434,\"outFeatures\":9}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 3574-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2866\nComponents:\n - input (input) params={\"shape\":[1,129]}\n - fc1 (linear) params={\"inFeatures\":129,\"outFeatures\":3574}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3574,\"outFeatures\":3574}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3574,\"outFeatures\":3574}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":3574,\"outFeatures\":34}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":129,\"outFeatures\":149}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":149,\"outFeatures\":149}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":149,\"outFeatures\":149}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":149,\"outFeatures\":34}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 236-feature, 53-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2867\nComponents:\n - input (input) params={\"shape\":[1,236]}\n - fc1 (linear) params={\"inFeatures\":236,\"outFeatures\":335}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":335,\"outFeatures\":339}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":339,\"outFeatures\":309}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":309,\"outFeatures\":53}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":335}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":339}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":309}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 249-feature user input and a 95-feature item input, each through its own 2-layer MLP tower ending at width 286, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2868\nComponents:\n - user_input (input) params={\"shape\":[1,249]}\n - item_input (input) params={\"shape\":[1,95]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,249]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,95]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":249,\"outFeatures\":286}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":286,\"outFeatures\":286}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":95,\"outFeatures\":286}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":286,\"outFeatures\":286}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":572,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (53-feature input, 11 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2869\nComponents:\n - input (input) params={\"shape\":[1,53]}\n - fc1 (linear) params={\"inFeatures\":53,\"outFeatures\":20}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":20,\"outFeatures\":20}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":20,\"outFeatures\":11}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":53,\"outFeatures\":972}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":972,\"outFeatures\":972}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":972,\"outFeatures\":11}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 129-feature input with 7 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2870\nComponents:\n - input (input) params={\"shape\":[1,129]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,129]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":129,\"outFeatures\":53}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":53,\"outFeatures\":569}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":569,\"outFeatures\":486}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":486,\"outFeatures\":7}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1718-dim input: encode down to a 222-dim bottleneck and decode back to 1718. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2871\nComponents:\n - input (input) params={\"shape\":[1,1718]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1718]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1718,\"outFeatures\":385}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":385,\"outFeatures\":222}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":222,\"outFeatures\":385}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":385,\"outFeatures\":1718}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x24x24 image with 22 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2872\nComponents:\n - input (input) params={\"shape\":[1,3,24,24]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,24,24]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":39,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":39,\"outChannels\":10,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":10,\"outFeatures\":22}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 367-token sequences with 89 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2873\nComponents:\n - input (input) params={\"shape\":[1,367]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,367]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":17570,\"embeddingDim\":192}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":192,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":192,\"outFeatures\":89}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 83-token sequences with 38 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2874\nComponents:\n - input (input) params={\"shape\":[1,83]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,83]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":49016,\"embeddingDim\":376}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":376,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[376]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":376,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[376]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":376,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[376]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":376,\"outFeatures\":38}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (194) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-2875\nComponents:\n - input (input) params={\"shape\":[1,337]}\n - embed (embedding) params={\"numEmbeddings\":21628,\"embeddingDim\":194}\n - attn (multiHeadAttention) params={\"embedDim\":194,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":194,\"outFeatures\":93}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3392-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2876\nComponents:\n - input (input) params={\"shape\":[1,212]}\n - fc1 (linear) params={\"inFeatures\":212,\"outFeatures\":3392}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3392,\"outFeatures\":3392}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3392,\"outFeatures\":3392}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3392,\"outFeatures\":3392}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3392,\"outFeatures\":39}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":212,\"outFeatures\":160}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":160,\"outFeatures\":160}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":160,\"outFeatures\":160}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":160,\"outFeatures\":160}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":160,\"outFeatures\":39}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 214-feature, 100-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2877\nComponents:\n - input (input) params={\"shape\":[1,214]}\n - fc1 (linear) params={\"inFeatures\":214,\"outFeatures\":306}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":306,\"outFeatures\":194}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":194,\"outFeatures\":83}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":83,\"outFeatures\":486}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":486,\"outFeatures\":100}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":306}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":194}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":83}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":486}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 226-feature user input and a 100-feature item input, each through its own 2-layer MLP tower ending at width 391, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2878\nComponents:\n - user_input (input) params={\"shape\":[1,226]}\n - item_input (input) params={\"shape\":[1,100]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,226]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,100]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":226,\"outFeatures\":391}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":391,\"outFeatures\":391}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":100,\"outFeatures\":391}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":391,\"outFeatures\":391}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":782,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (68-feature input, 38 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2879\nComponents:\n - input (input) params={\"shape\":[1,68]}\n - fc1 (linear) params={\"inFeatures\":68,\"outFeatures\":16}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":16,\"outFeatures\":16}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":16,\"outFeatures\":38}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":68,\"outFeatures\":967}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":967,\"outFeatures\":967}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":967,\"outFeatures\":38}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 51-feature input with 81 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2880\nComponents:\n - input (input) params={\"shape\":[1,51]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,51]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":51,\"outFeatures\":412}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":412,\"outFeatures\":979}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":979,\"outFeatures\":971}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":971,\"outFeatures\":427}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":427,\"outFeatures\":97}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":97,\"outFeatures\":31}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":31,\"outFeatures\":81}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 177-dim input: encode down to a 216-dim bottleneck and decode back to 177. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2881\nComponents:\n - input (input) params={\"shape\":[1,177]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,177]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":177,\"outFeatures\":541}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":541,\"outFeatures\":216}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":216,\"outFeatures\":541}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":541,\"outFeatures\":177}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x41x41 image with 47 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2882\nComponents:\n - input (input) params={\"shape\":[1,3,41,41]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,41,41]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":56,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":56,\"outChannels\":28,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":28,\"outChannels\":40,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":40,\"outFeatures\":47}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 100-token sequences with 33 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2883\nComponents:\n - input (input) params={\"shape\":[1,100]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,100]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":33362,\"embeddingDim\":456}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":456,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":456,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":456,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":456,\"outFeatures\":33}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 495-token sequences with 63 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2884\nComponents:\n - input (input) params={\"shape\":[1,495]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,495]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":32812,\"embeddingDim\":140}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":140,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[140]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":140,\"outFeatures\":63}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (398) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-2885\nComponents:\n - input (input) params={\"shape\":[1,373]}\n - embed (embedding) params={\"numEmbeddings\":25009,\"embeddingDim\":398}\n - attn (multiHeadAttention) params={\"embedDim\":398,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":398,\"outFeatures\":94}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 3486-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2886\nComponents:\n - input (input) params={\"shape\":[1,234]}\n - fc1 (linear) params={\"inFeatures\":234,\"outFeatures\":3486}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3486,\"outFeatures\":3486}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":3486,\"outFeatures\":31}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":234,\"outFeatures\":108}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":108,\"outFeatures\":108}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":108,\"outFeatures\":31}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 226-feature, 16-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2887\nComponents:\n - input (input) params={\"shape\":[1,226]}\n - fc1 (linear) params={\"inFeatures\":226,\"outFeatures\":416}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":416,\"outFeatures\":223}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":223,\"outFeatures\":16}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":416}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":223}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 245-feature user input and a 83-feature item input, each through its own 2-layer MLP tower ending at width 375, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2888\nComponents:\n - user_input (input) params={\"shape\":[1,245]}\n - item_input (input) params={\"shape\":[1,83]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,245]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,83]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":245,\"outFeatures\":375}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":375,\"outFeatures\":375}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":83,\"outFeatures\":375}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":375,\"outFeatures\":375}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":750,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (109-feature input, 6 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2889\nComponents:\n - input (input) params={\"shape\":[1,109]}\n - fc1 (linear) params={\"inFeatures\":109,\"outFeatures\":12}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":12,\"outFeatures\":12}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":12,\"outFeatures\":6}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":109,\"outFeatures\":686}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":686,\"outFeatures\":686}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":686,\"outFeatures\":6}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 153-feature input with 41 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2890\nComponents:\n - input (input) params={\"shape\":[1,153]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,153]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":153,\"outFeatures\":504}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":504,\"outFeatures\":901}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":901,\"outFeatures\":459}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":459,\"outFeatures\":622}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":622,\"outFeatures\":584}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":584,\"outFeatures\":111}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":111,\"outFeatures\":41}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 648-dim input: encode down to a 240-dim bottleneck and decode back to 648. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2891\nComponents:\n - input (input) params={\"shape\":[1,648]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,648]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":648,\"outFeatures\":172}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":172,\"outFeatures\":240}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":240,\"outFeatures\":172}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":172,\"outFeatures\":648}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x29x29 image with 80 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2892\nComponents:\n - input (input) params={\"shape\":[1,3,29,29]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,29,29]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":17,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":17,\"outChannels\":48,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":48,\"outFeatures\":80}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 504-token sequences with 59 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2893\nComponents:\n - input (input) params={\"shape\":[1,504]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,504]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":42544,\"embeddingDim\":84}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":84,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":84,\"outFeatures\":59}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 183-token sequences with 72 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2894\nComponents:\n - input (input) params={\"shape\":[1,183]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,183]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":31625,\"embeddingDim\":560}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":560,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[560]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":560,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[560]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":560,\"outFeatures\":72}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 2141-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2896\nComponents:\n - input (input) params={\"shape\":[1,146]}\n - fc1 (linear) params={\"inFeatures\":146,\"outFeatures\":2141}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2141,\"outFeatures\":2141}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2141,\"outFeatures\":2141}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":2141,\"outFeatures\":2141}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":2141,\"outFeatures\":2}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":146,\"outFeatures\":372}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":372,\"outFeatures\":372}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":372,\"outFeatures\":372}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":372,\"outFeatures\":372}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":372,\"outFeatures\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 29-feature, 27-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2897\nComponents:\n - input (input) params={\"shape\":[1,29]}\n - fc1 (linear) params={\"inFeatures\":29,\"outFeatures\":200}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":200,\"outFeatures\":478}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":478,\"outFeatures\":27}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":200}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":478}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 130-feature user input and a 136-feature item input, each through its own 2-layer MLP tower ending at width 255, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2898\nComponents:\n - user_input (input) params={\"shape\":[1,130]}\n - item_input (input) params={\"shape\":[1,136]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,130]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,136]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":130,\"outFeatures\":255}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":255,\"outFeatures\":255}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":136,\"outFeatures\":255}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":255,\"outFeatures\":255}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":510,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (101-feature input, 14 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2899\nComponents:\n - input (input) params={\"shape\":[1,101]}\n - fc1 (linear) params={\"inFeatures\":101,\"outFeatures\":14}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":14,\"outFeatures\":14}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":14,\"outFeatures\":14}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":101,\"outFeatures\":1302}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1302,\"outFeatures\":1302}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1302,\"outFeatures\":14}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 428-feature input with 102 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2900\nComponents:\n - input (input) params={\"shape\":[1,428]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,428]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":428,\"outFeatures\":578}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":578,\"outFeatures\":486}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":486,\"outFeatures\":249}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":249,\"outFeatures\":581}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":581,\"outFeatures\":487}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":487,\"outFeatures\":102}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1253-dim input: encode down to a 10-dim bottleneck and decode back to 1253. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2901\nComponents:\n - input (input) params={\"shape\":[1,1253]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1253]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1253,\"outFeatures\":376}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":376,\"outFeatures\":10}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":10,\"outFeatures\":376}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":376,\"outFeatures\":1253}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x32x32 image with 65 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2902\nComponents:\n - input (input) params={\"shape\":[1,3,32,32]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,32,32]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":39,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":39,\"outChannels\":17,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":17,\"outFeatures\":65}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 243-token sequences with 65 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2903\nComponents:\n - input (input) params={\"shape\":[1,243]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,243]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":26550,\"embeddingDim\":176}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":176,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":176,\"outFeatures\":65}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 480-token sequences with 82 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2904\nComponents:\n - input (input) params={\"shape\":[1,480]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,480]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":40111,\"embeddingDim\":192}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":192,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[192]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":192,\"outFeatures\":82}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 2113-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2906\nComponents:\n - input (input) params={\"shape\":[1,181]}\n - fc1 (linear) params={\"inFeatures\":181,\"outFeatures\":2113}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2113,\"outFeatures\":2113}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":2113,\"outFeatures\":37}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":181,\"outFeatures\":267}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":267,\"outFeatures\":267}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":267,\"outFeatures\":37}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 143-feature, 96-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2907\nComponents:\n - input (input) params={\"shape\":[1,143]}\n - fc1 (linear) params={\"inFeatures\":143,\"outFeatures\":386}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":386,\"outFeatures\":350}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":350,\"outFeatures\":96}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":386}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":350}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 144-feature user input and a 109-feature item input, each through its own 2-layer MLP tower ending at width 318, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2908\nComponents:\n - user_input (input) params={\"shape\":[1,144]}\n - item_input (input) params={\"shape\":[1,109]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,144]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,109]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":144,\"outFeatures\":318}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":318,\"outFeatures\":318}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":109,\"outFeatures\":318}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":318,\"outFeatures\":318}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":636,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (109-feature input, 33 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2909\nComponents:\n - input (input) params={\"shape\":[1,109]}\n - fc1 (linear) params={\"inFeatures\":109,\"outFeatures\":16}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":16,\"outFeatures\":16}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":16,\"outFeatures\":33}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":109,\"outFeatures\":643}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":643,\"outFeatures\":643}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":643,\"outFeatures\":33}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 61-feature input with 66 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2910\nComponents:\n - input (input) params={\"shape\":[1,61]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,61]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":61,\"outFeatures\":485}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":485,\"outFeatures\":619}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":619,\"outFeatures\":816}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":816,\"outFeatures\":31}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":31,\"outFeatures\":66}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 314-dim input: encode down to a 143-dim bottleneck and decode back to 314. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2911\nComponents:\n - input (input) params={\"shape\":[1,314]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,314]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":314,\"outFeatures\":152}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":152,\"outFeatures\":143}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":143,\"outFeatures\":152}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":152,\"outFeatures\":314}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x44x44 image with 87 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2912\nComponents:\n - input (input) params={\"shape\":[1,3,44,44]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,44,44]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":54,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":54,\"outChannels\":45,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":45,\"outFeatures\":87}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 66-token sequences with 46 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2913\nComponents:\n - input (input) params={\"shape\":[1,66]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,66]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":34716,\"embeddingDim\":72}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":72,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":72,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":72,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":72,\"outFeatures\":46}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 341-token sequences with 69 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2914\nComponents:\n - input (input) params={\"shape\":[1,341]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,341]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":19129,\"embeddingDim\":736}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":736,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[736]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":736,\"outFeatures\":69}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (428) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-2915\nComponents:\n - input (input) params={\"shape\":[1,343]}\n - embed (embedding) params={\"numEmbeddings\":8943,\"embeddingDim\":428}\n - attn (multiHeadAttention) params={\"embedDim\":428,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":428,\"outFeatures\":81}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":4}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 2718-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2916\nComponents:\n - input (input) params={\"shape\":[1,123]}\n - fc1 (linear) params={\"inFeatures\":123,\"outFeatures\":2718}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2718,\"outFeatures\":2718}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2718,\"outFeatures\":2718}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":2718,\"outFeatures\":19}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":123,\"outFeatures\":355}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":355,\"outFeatures\":355}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":355,\"outFeatures\":355}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":355,\"outFeatures\":19}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 83-feature, 7-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2917\nComponents:\n - input (input) params={\"shape\":[1,83]}\n - fc1 (linear) params={\"inFeatures\":83,\"outFeatures\":360}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":360,\"outFeatures\":98}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":98,\"outFeatures\":437}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":437,\"outFeatures\":214}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":214,\"outFeatures\":254}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":254,\"outFeatures\":7}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":360}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":98}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":437}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":214}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":254}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 47-feature user input and a 214-feature item input, each through its own 2-layer MLP tower ending at width 39, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2918\nComponents:\n - user_input (input) params={\"shape\":[1,47]}\n - item_input (input) params={\"shape\":[1,214]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,47]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,214]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":47,\"outFeatures\":39}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":39,\"outFeatures\":39}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":214,\"outFeatures\":39}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":39,\"outFeatures\":39}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":78,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (59-feature input, 29 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2919\nComponents:\n - input (input) params={\"shape\":[1,59]}\n - fc1 (linear) params={\"inFeatures\":59,\"outFeatures\":19}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":19,\"outFeatures\":19}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":19,\"outFeatures\":29}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":59,\"outFeatures\":1026}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1026,\"outFeatures\":1026}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1026,\"outFeatures\":29}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 175-feature input with 176 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2920\nComponents:\n - input (input) params={\"shape\":[1,175]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,175]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":175,\"outFeatures\":674}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":674,\"outFeatures\":560}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":560,\"outFeatures\":224}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":224,\"outFeatures\":686}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":686,\"outFeatures\":176}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 361-dim input: encode down to a 53-dim bottleneck and decode back to 361. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2921\nComponents:\n - input (input) params={\"shape\":[1,361]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,361]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":361,\"outFeatures\":514}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":514,\"outFeatures\":53}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":53,\"outFeatures\":514}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":514,\"outFeatures\":361}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x34x34 image with 79 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2922\nComponents:\n - input (input) params={\"shape\":[1,3,34,34]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,34,34]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":16,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":16,\"outChannels\":14,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":14,\"outChannels\":39,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":39,\"outChannels\":26,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":26,\"outFeatures\":79}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 232-token sequences with 26 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2923\nComponents:\n - input (input) params={\"shape\":[1,232]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,232]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":42163,\"embeddingDim\":120}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":120,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":120,\"outFeatures\":26}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 297-token sequences with 25 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2924\nComponents:\n - input (input) params={\"shape\":[1,297]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,297]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":40009,\"embeddingDim\":608}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":608,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[608]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":608,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[608]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":608,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[608]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":608,\"outFeatures\":25}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 3257-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2926\nComponents:\n - input (input) params={\"shape\":[1,66]}\n - fc1 (linear) params={\"inFeatures\":66,\"outFeatures\":3257}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3257,\"outFeatures\":3257}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3257,\"outFeatures\":3257}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":3257,\"outFeatures\":21}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":66,\"outFeatures\":317}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":317,\"outFeatures\":317}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":317,\"outFeatures\":317}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":317,\"outFeatures\":21}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 212-feature, 38-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2927\nComponents:\n - input (input) params={\"shape\":[1,212]}\n - fc1 (linear) params={\"inFeatures\":212,\"outFeatures\":510}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":510,\"outFeatures\":45}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":45,\"outFeatures\":179}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":179,\"outFeatures\":38}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":510}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":45}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":179}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 248-feature user input and a 154-feature item input, each through its own 2-layer MLP tower ending at width 349, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2928\nComponents:\n - user_input (input) params={\"shape\":[1,248]}\n - item_input (input) params={\"shape\":[1,154]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,248]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,154]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":248,\"outFeatures\":349}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":349,\"outFeatures\":349}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":154,\"outFeatures\":349}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":349,\"outFeatures\":349}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":698,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (62-feature input, 46 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2929\nComponents:\n - input (input) params={\"shape\":[1,62]}\n - fc1 (linear) params={\"inFeatures\":62,\"outFeatures\":13}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":13,\"outFeatures\":13}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":13,\"outFeatures\":46}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":62,\"outFeatures\":851}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":851,\"outFeatures\":851}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":851,\"outFeatures\":46}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 422-feature input with 195 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2930\nComponents:\n - input (input) params={\"shape\":[1,422]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,422]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":422,\"outFeatures\":756}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":756,\"outFeatures\":112}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":112,\"outFeatures\":195}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 565-dim input: encode down to a 216-dim bottleneck and decode back to 565. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2931\nComponents:\n - input (input) params={\"shape\":[1,565]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,565]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":565,\"outFeatures\":810}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":810,\"outFeatures\":216}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":216,\"outFeatures\":810}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":810,\"outFeatures\":565}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x63x63 image with 89 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2932\nComponents:\n - input (input) params={\"shape\":[1,3,63,63]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,63,63]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":15,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":15,\"outChannels\":21,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":21,\"outChannels\":17,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":17,\"outFeatures\":89}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 326-token sequences with 28 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2933\nComponents:\n - input (input) params={\"shape\":[1,326]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,326]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":42849,\"embeddingDim\":232}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":232,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":232,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":232,\"outFeatures\":28}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 402-token sequences with 16 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2934\nComponents:\n - input (input) params={\"shape\":[1,402]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,402]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":20267,\"embeddingDim\":336}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":336,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[336]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":336,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[336]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":336,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[336]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":336,\"outFeatures\":16}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 2664-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2936\nComponents:\n - input (input) params={\"shape\":[1,114]}\n - fc1 (linear) params={\"inFeatures\":114,\"outFeatures\":2664}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2664,\"outFeatures\":2664}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":2664,\"outFeatures\":33}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":114,\"outFeatures\":169}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":169,\"outFeatures\":169}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":169,\"outFeatures\":33}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 56-feature, 30-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2937\nComponents:\n - input (input) params={\"shape\":[1,56]}\n - fc1 (linear) params={\"inFeatures\":56,\"outFeatures\":56}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":56,\"outFeatures\":202}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":202,\"outFeatures\":384}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":384,\"outFeatures\":401}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":401,\"outFeatures\":480}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":480,\"outFeatures\":30}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":56}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":202}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":384}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":401}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":480}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 26-feature user input and a 20-feature item input, each through its own 2-layer MLP tower ending at width 335, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2938\nComponents:\n - user_input (input) params={\"shape\":[1,26]}\n - item_input (input) params={\"shape\":[1,20]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,26]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,20]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":26,\"outFeatures\":335}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":335,\"outFeatures\":335}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":20,\"outFeatures\":335}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":335,\"outFeatures\":335}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":670,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (27-feature input, 48 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2939\nComponents:\n - input (input) params={\"shape\":[1,27]}\n - fc1 (linear) params={\"inFeatures\":27,\"outFeatures\":7}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":7,\"outFeatures\":7}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":7,\"outFeatures\":48}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":27,\"outFeatures\":783}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":783,\"outFeatures\":783}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":783,\"outFeatures\":48}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 113-feature input with 82 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2940\nComponents:\n - input (input) params={\"shape\":[1,113]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,113]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":113,\"outFeatures\":717}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":717,\"outFeatures\":888}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":888,\"outFeatures\":842}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":842,\"outFeatures\":82}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 579-dim input: encode down to a 116-dim bottleneck and decode back to 579. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2941\nComponents:\n - input (input) params={\"shape\":[1,579]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,579]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":579,\"outFeatures\":758}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":758,\"outFeatures\":116}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":116,\"outFeatures\":758}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":758,\"outFeatures\":579}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x37x37 image with 28 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2942\nComponents:\n - input (input) params={\"shape\":[1,3,37,37]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,37,37]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":24,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":24,\"outChannels\":64,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":64,\"outChannels\":19,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":19,\"outChannels\":22,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":22,\"outFeatures\":28}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 370-token sequences with 58 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2943\nComponents:\n - input (input) params={\"shape\":[1,370]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,370]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":14139,\"embeddingDim\":48}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":48,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":48,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":48,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":48,\"outFeatures\":58}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 96-token sequences with 3 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2944\nComponents:\n - input (input) params={\"shape\":[1,96]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,96]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":17643,\"embeddingDim\":432}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":432,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[432]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":432,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[432]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":432,\"outFeatures\":3}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (328) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-2945\nComponents:\n - input (input) params={\"shape\":[1,243]}\n - embed (embedding) params={\"numEmbeddings\":9963,\"embeddingDim\":328}\n - attn (multiHeadAttention) params={\"embedDim\":328,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":328,\"outFeatures\":79}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":8}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 3005-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2946\nComponents:\n - input (input) params={\"shape\":[1,137]}\n - fc1 (linear) params={\"inFeatures\":137,\"outFeatures\":3005}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3005,\"outFeatures\":3005}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3005,\"outFeatures\":3005}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":3005,\"outFeatures\":47}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":137,\"outFeatures\":319}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":319,\"outFeatures\":319}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":319,\"outFeatures\":319}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":319,\"outFeatures\":47}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 255-feature, 73-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2947\nComponents:\n - input (input) params={\"shape\":[1,255]}\n - fc1 (linear) params={\"inFeatures\":255,\"outFeatures\":284}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":284,\"outFeatures\":445}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":445,\"outFeatures\":73}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":284}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":445}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 255-feature user input and a 38-feature item input, each through its own 2-layer MLP tower ending at width 86, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2948\nComponents:\n - user_input (input) params={\"shape\":[1,255]}\n - item_input (input) params={\"shape\":[1,38]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,255]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,38]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":255,\"outFeatures\":86}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":86,\"outFeatures\":86}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":38,\"outFeatures\":86}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":86,\"outFeatures\":86}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":172,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (28-feature input, 24 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2949\nComponents:\n - input (input) params={\"shape\":[1,28]}\n - fc1 (linear) params={\"inFeatures\":28,\"outFeatures\":9}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":9,\"outFeatures\":9}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":9,\"outFeatures\":24}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":28,\"outFeatures\":858}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":858,\"outFeatures\":858}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":858,\"outFeatures\":24}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 324-feature input with 7 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2950\nComponents:\n - input (input) params={\"shape\":[1,324]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,324]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":324,\"outFeatures\":530}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":530,\"outFeatures\":995}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":995,\"outFeatures\":756}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":756,\"outFeatures\":544}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":544,\"outFeatures\":7}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1595-dim input: encode down to a 165-dim bottleneck and decode back to 1595. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2951\nComponents:\n - input (input) params={\"shape\":[1,1595]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1595]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1595,\"outFeatures\":954}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":954,\"outFeatures\":165}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":165,\"outFeatures\":954}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":954,\"outFeatures\":1595}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x31x31 image with 69 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2952\nComponents:\n - input (input) params={\"shape\":[1,3,31,31]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,31,31]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":47,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":47,\"outChannels\":14,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":14,\"outChannels\":51,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":51,\"outFeatures\":69}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 228-token sequences with 59 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2953\nComponents:\n - input (input) params={\"shape\":[1,228]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,228]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":18837,\"embeddingDim\":148}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":148,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":148,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":148,\"outFeatures\":59}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 272-token sequences with 21 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2954\nComponents:\n - input (input) params={\"shape\":[1,272]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,272]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":13225,\"embeddingDim\":192}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":192,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[192]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":192,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[192]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":192,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[192]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":192,\"outFeatures\":21}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (306) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-2955\nComponents:\n - input (input) params={\"shape\":[1,134]}\n - embed (embedding) params={\"numEmbeddings\":15871,\"embeddingDim\":306}\n - attn (multiHeadAttention) params={\"embedDim\":306,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":306,\"outFeatures\":72}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 4011-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2956\nComponents:\n - input (input) params={\"shape\":[1,216]}\n - fc1 (linear) params={\"inFeatures\":216,\"outFeatures\":4011}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":4011,\"outFeatures\":4011}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":4011,\"outFeatures\":4011}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":4011,\"outFeatures\":4011}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":4011,\"outFeatures\":12}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":216,\"outFeatures\":358}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":358,\"outFeatures\":358}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":358,\"outFeatures\":358}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":358,\"outFeatures\":358}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":358,\"outFeatures\":12}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 72-feature, 78-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2957\nComponents:\n - input (input) params={\"shape\":[1,72]}\n - fc1 (linear) params={\"inFeatures\":72,\"outFeatures\":230}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":230,\"outFeatures\":322}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":322,\"outFeatures\":397}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":397,\"outFeatures\":136}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":136,\"outFeatures\":343}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":343,\"outFeatures\":78}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":230}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":322}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":397}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":136}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":343}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 46-feature user input and a 182-feature item input, each through its own 2-layer MLP tower ending at width 62, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2958\nComponents:\n - user_input (input) params={\"shape\":[1,46]}\n - item_input (input) params={\"shape\":[1,182]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,46]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,182]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":46,\"outFeatures\":62}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":62,\"outFeatures\":62}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":182,\"outFeatures\":62}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":62,\"outFeatures\":62}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":124,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (50-feature input, 14 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2959\nComponents:\n - input (input) params={\"shape\":[1,50]}\n - fc1 (linear) params={\"inFeatures\":50,\"outFeatures\":12}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":12,\"outFeatures\":12}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":12,\"outFeatures\":14}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":50,\"outFeatures\":641}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":641,\"outFeatures\":641}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":641,\"outFeatures\":14}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 368-feature input with 57 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2960\nComponents:\n - input (input) params={\"shape\":[1,368]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,368]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":368,\"outFeatures\":915}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":915,\"outFeatures\":999}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":999,\"outFeatures\":243}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":243,\"outFeatures\":151}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":151,\"outFeatures\":905}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":905,\"outFeatures\":57}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 649-dim input: encode down to a 176-dim bottleneck and decode back to 649. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2961\nComponents:\n - input (input) params={\"shape\":[1,649]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,649]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":649,\"outFeatures\":409}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":409,\"outFeatures\":176}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":176,\"outFeatures\":409}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":409,\"outFeatures\":649}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x32x32 image with 27 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2962\nComponents:\n - input (input) params={\"shape\":[1,3,32,32]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,32,32]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":62,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":62,\"outChannels\":26,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":26,\"outChannels\":23,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":23,\"outChannels\":13,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":13,\"outFeatures\":27}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 141-token sequences with 81 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2963\nComponents:\n - input (input) params={\"shape\":[1,141]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,141]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":17113,\"embeddingDim\":136}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":136,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":136,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":136,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":136,\"outFeatures\":81}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 43-token sequences with 39 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2964\nComponents:\n - input (input) params={\"shape\":[1,43]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,43]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":38508,\"embeddingDim\":400}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":400,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[400]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":400,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[400]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":400,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[400]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":400,\"outFeatures\":39}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (512) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-2965\nComponents:\n - input (input) params={\"shape\":[1,128]}\n - embed (embedding) params={\"numEmbeddings\":12124,\"embeddingDim\":512}\n - attn (multiHeadAttention) params={\"embedDim\":512,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":512,\"outFeatures\":68}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":16}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 3201-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2966\nComponents:\n - input (input) params={\"shape\":[1,138]}\n - fc1 (linear) params={\"inFeatures\":138,\"outFeatures\":3201}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3201,\"outFeatures\":3201}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":3201,\"outFeatures\":11}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":138,\"outFeatures\":124}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":124,\"outFeatures\":124}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":124,\"outFeatures\":11}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 115-feature, 67-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2967\nComponents:\n - input (input) params={\"shape\":[1,115]}\n - fc1 (linear) params={\"inFeatures\":115,\"outFeatures\":499}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":499,\"outFeatures\":119}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":119,\"outFeatures\":253}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":253,\"outFeatures\":216}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":216,\"outFeatures\":253}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":253,\"outFeatures\":67}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":499}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":119}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":253}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":216}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":253}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 228-feature user input and a 76-feature item input, each through its own 2-layer MLP tower ending at width 448, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2968\nComponents:\n - user_input (input) params={\"shape\":[1,228]}\n - item_input (input) params={\"shape\":[1,76]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,228]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,76]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":228,\"outFeatures\":448}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":448,\"outFeatures\":448}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":76,\"outFeatures\":448}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":448,\"outFeatures\":448}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":896,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (68-feature input, 8 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2969\nComponents:\n - input (input) params={\"shape\":[1,68]}\n - fc1 (linear) params={\"inFeatures\":68,\"outFeatures\":15}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":15,\"outFeatures\":15}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":15,\"outFeatures\":8}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":68,\"outFeatures\":801}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":801,\"outFeatures\":801}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":801,\"outFeatures\":8}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 330-feature input with 57 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2970\nComponents:\n - input (input) params={\"shape\":[1,330]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,330]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":330,\"outFeatures\":685}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":685,\"outFeatures\":31}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":31,\"outFeatures\":765}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":765,\"outFeatures\":529}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":529,\"outFeatures\":906}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":906,\"outFeatures\":57}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 883-dim input: encode down to a 19-dim bottleneck and decode back to 883. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2971\nComponents:\n - input (input) params={\"shape\":[1,883]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,883]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":883,\"outFeatures\":883}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":883,\"outFeatures\":19}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":19,\"outFeatures\":883}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":883,\"outFeatures\":883}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x37x37 image with 69 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2972\nComponents:\n - input (input) params={\"shape\":[1,3,37,37]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,37,37]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":10,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":10,\"outChannels\":59,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":59,\"outChannels\":19,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":19,\"outFeatures\":69}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 332-token sequences with 30 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2973\nComponents:\n - input (input) params={\"shape\":[1,332]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,332]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":41657,\"embeddingDim\":208}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":208,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":208,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":208,\"outFeatures\":30}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 459-token sequences with 8 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2974\nComponents:\n - input (input) params={\"shape\":[1,459]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,459]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":45871,\"embeddingDim\":136}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":136,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[136]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":136,\"outFeatures\":8}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 3359-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2976\nComponents:\n - input (input) params={\"shape\":[1,254]}\n - fc1 (linear) params={\"inFeatures\":254,\"outFeatures\":3359}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3359,\"outFeatures\":3359}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3359,\"outFeatures\":3359}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":3359,\"outFeatures\":26}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":254,\"outFeatures\":210}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":210,\"outFeatures\":210}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":210,\"outFeatures\":210}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":210,\"outFeatures\":26}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 201-feature, 30-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2977\nComponents:\n - input (input) params={\"shape\":[1,201]}\n - fc1 (linear) params={\"inFeatures\":201,\"outFeatures\":279}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":279,\"outFeatures\":490}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":490,\"outFeatures\":30}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":279}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":490}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 138-feature user input and a 170-feature item input, each through its own 2-layer MLP tower ending at width 368, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2978\nComponents:\n - user_input (input) params={\"shape\":[1,138]}\n - item_input (input) params={\"shape\":[1,170]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,138]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,170]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":138,\"outFeatures\":368}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":368,\"outFeatures\":368}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":170,\"outFeatures\":368}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":368,\"outFeatures\":368}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":736,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (82-feature input, 42 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2979\nComponents:\n - input (input) params={\"shape\":[1,82]}\n - fc1 (linear) params={\"inFeatures\":82,\"outFeatures\":9}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":9,\"outFeatures\":9}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":9,\"outFeatures\":42}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":82,\"outFeatures\":870}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":870,\"outFeatures\":870}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":870,\"outFeatures\":42}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 276-feature input with 59 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2980\nComponents:\n - input (input) params={\"shape\":[1,276]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,276]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":276,\"outFeatures\":681}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":681,\"outFeatures\":601}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":601,\"outFeatures\":576}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":576,\"outFeatures\":82}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":82,\"outFeatures\":715}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":715,\"outFeatures\":133}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":133,\"outFeatures\":59}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 714-dim input: encode down to a 191-dim bottleneck and decode back to 714. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2981\nComponents:\n - input (input) params={\"shape\":[1,714]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,714]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":714,\"outFeatures\":1017}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":1017,\"outFeatures\":191}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":191,\"outFeatures\":1017}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":1017,\"outFeatures\":714}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x34x34 image with 83 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2982\nComponents:\n - input (input) params={\"shape\":[1,3,34,34]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,34,34]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":10,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":10,\"outChannels\":21,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":21,\"outFeatures\":83}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 301-token sequences with 67 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2983\nComponents:\n - input (input) params={\"shape\":[1,301]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,301]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":49359,\"embeddingDim\":136}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":136,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":136,\"outFeatures\":67}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 491-token sequences with 60 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2984\nComponents:\n - input (input) params={\"shape\":[1,491]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,491]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":33165,\"embeddingDim\":124}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":124,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[124]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":124,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[124]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":124,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[124]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":124,\"outFeatures\":60}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 3714-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2986\nComponents:\n - input (input) params={\"shape\":[1,149]}\n - fc1 (linear) params={\"inFeatures\":149,\"outFeatures\":3714}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3714,\"outFeatures\":3714}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":3714,\"outFeatures\":36}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":149,\"outFeatures\":316}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":316,\"outFeatures\":316}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":316,\"outFeatures\":36}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 175-feature, 8-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2987\nComponents:\n - input (input) params={\"shape\":[1,175]}\n - fc1 (linear) params={\"inFeatures\":175,\"outFeatures\":346}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":346,\"outFeatures\":439}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":439,\"outFeatures\":8}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":346}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":439}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 112-feature user input and a 93-feature item input, each through its own 2-layer MLP tower ending at width 280, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2988\nComponents:\n - user_input (input) params={\"shape\":[1,112]}\n - item_input (input) params={\"shape\":[1,93]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,112]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,93]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":112,\"outFeatures\":280}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":280,\"outFeatures\":280}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":93,\"outFeatures\":280}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":280,\"outFeatures\":280}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":560,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (38-feature input, 5 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2989\nComponents:\n - input (input) params={\"shape\":[1,38]}\n - fc1 (linear) params={\"inFeatures\":38,\"outFeatures\":14}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":14,\"outFeatures\":14}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":14,\"outFeatures\":5}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":38,\"outFeatures\":646}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":646,\"outFeatures\":646}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":646,\"outFeatures\":5}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 13-feature input with 31 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-2990\nComponents:\n - input (input) params={\"shape\":[1,13]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,13]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":13,\"outFeatures\":661}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":661,\"outFeatures\":386}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":386,\"outFeatures\":31}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 945-dim input: encode down to a 227-dim bottleneck and decode back to 945. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-2991\nComponents:\n - input (input) params={\"shape\":[1,945]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,945]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":945,\"outFeatures\":359}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":359,\"outFeatures\":227}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":227,\"outFeatures\":359}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":359,\"outFeatures\":945}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x64x64 image with 50 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-2992\nComponents:\n - input (input) params={\"shape\":[1,3,64,64]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,64,64]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":26,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":26,\"outChannels\":13,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":13,\"outFeatures\":50}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 300-token sequences with 49 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-2993\nComponents:\n - input (input) params={\"shape\":[1,300]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,300]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":17089,\"embeddingDim\":160}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":160,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":160,\"outFeatures\":49}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 282-token sequences with 78 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-2994\nComponents:\n - input (input) params={\"shape\":[1,282]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,282]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":37953,\"embeddingDim\":80}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":80,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[80]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":80,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[80]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":80,\"outFeatures\":78}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (366) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-2995\nComponents:\n - input (input) params={\"shape\":[1,123]}\n - embed (embedding) params={\"numEmbeddings\":44954,\"embeddingDim\":366}\n - attn (multiHeadAttention) params={\"embedDim\":366,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":366,\"outFeatures\":70}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 2322-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-2996\nComponents:\n - input (input) params={\"shape\":[1,133]}\n - fc1 (linear) params={\"inFeatures\":133,\"outFeatures\":2322}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2322,\"outFeatures\":2322}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2322,\"outFeatures\":2322}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":2322,\"outFeatures\":16}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":133,\"outFeatures\":223}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":223,\"outFeatures\":223}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":223,\"outFeatures\":223}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":223,\"outFeatures\":16}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 215-feature, 91-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-2997\nComponents:\n - input (input) params={\"shape\":[1,215]}\n - fc1 (linear) params={\"inFeatures\":215,\"outFeatures\":278}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":278,\"outFeatures\":89}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":89,\"outFeatures\":55}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":55,\"outFeatures\":135}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":135,\"outFeatures\":410}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":410,\"outFeatures\":91}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":278}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":89}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":55}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":135}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":410}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 201-feature user input and a 42-feature item input, each through its own 2-layer MLP tower ending at width 460, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-2998\nComponents:\n - user_input (input) params={\"shape\":[1,201]}\n - item_input (input) params={\"shape\":[1,42]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,201]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,42]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":201,\"outFeatures\":460}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":460,\"outFeatures\":460}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":42,\"outFeatures\":460}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":460,\"outFeatures\":460}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":920,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (63-feature input, 47 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-2999\nComponents:\n - input (input) params={\"shape\":[1,63]}\n - fc1 (linear) params={\"inFeatures\":63,\"outFeatures\":12}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":12,\"outFeatures\":12}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":12,\"outFeatures\":47}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":63,\"outFeatures\":1167}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1167,\"outFeatures\":1167}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1167,\"outFeatures\":47}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 449-feature input with 97 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-3000\nComponents:\n - input (input) params={\"shape\":[1,449]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,449]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":449,\"outFeatures\":383}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":383,\"outFeatures\":630}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":630,\"outFeatures\":97}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 822-dim input: encode down to a 172-dim bottleneck and decode back to 822. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-3001\nComponents:\n - input (input) params={\"shape\":[1,822]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,822]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":822,\"outFeatures\":501}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":501,\"outFeatures\":172}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":172,\"outFeatures\":501}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":501,\"outFeatures\":822}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x50x50 image with 33 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-3002\nComponents:\n - input (input) params={\"shape\":[1,3,50,50]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,50,50]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":14,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":14,\"outChannels\":29,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":29,\"outChannels\":52,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":52,\"outFeatures\":33}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 99-token sequences with 39 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-3003\nComponents:\n - input (input) params={\"shape\":[1,99]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,99]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":39104,\"embeddingDim\":88}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":88,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":88,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":88,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":88,\"outFeatures\":39}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 238-token sequences with 92 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-3004\nComponents:\n - input (input) params={\"shape\":[1,238]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,238]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":47186,\"embeddingDim\":368}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":368,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[368]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":368,\"outFeatures\":92}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (484) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-3005\nComponents:\n - input (input) params={\"shape\":[1,204]}\n - embed (embedding) params={\"numEmbeddings\":44075,\"embeddingDim\":484}\n - attn (multiHeadAttention) params={\"embedDim\":484,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":484,\"outFeatures\":92}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":4}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 1595-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-3006\nComponents:\n - input (input) params={\"shape\":[1,50]}\n - fc1 (linear) params={\"inFeatures\":50,\"outFeatures\":1595}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":1595,\"outFeatures\":1595}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":1595,\"outFeatures\":1595}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":1595,\"outFeatures\":18}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":50,\"outFeatures\":68}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":68,\"outFeatures\":68}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":68,\"outFeatures\":68}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":68,\"outFeatures\":18}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 210-feature, 24-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-3007\nComponents:\n - input (input) params={\"shape\":[1,210]}\n - fc1 (linear) params={\"inFeatures\":210,\"outFeatures\":491}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":491,\"outFeatures\":271}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":271,\"outFeatures\":165}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":165,\"outFeatures\":24}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":491}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":271}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":165}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 19-feature user input and a 45-feature item input, each through its own 2-layer MLP tower ending at width 160, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-3008\nComponents:\n - user_input (input) params={\"shape\":[1,19]}\n - item_input (input) params={\"shape\":[1,45]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,19]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,45]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":19,\"outFeatures\":160}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":160,\"outFeatures\":160}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":45,\"outFeatures\":160}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":160,\"outFeatures\":160}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":320,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (95-feature input, 7 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-3009\nComponents:\n - input (input) params={\"shape\":[1,95]}\n - fc1 (linear) params={\"inFeatures\":95,\"outFeatures\":9}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":9,\"outFeatures\":9}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":9,\"outFeatures\":7}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":95,\"outFeatures\":1377}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1377,\"outFeatures\":1377}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1377,\"outFeatures\":7}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 193-feature input with 28 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-3010\nComponents:\n - input (input) params={\"shape\":[1,193]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,193]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":193,\"outFeatures\":839}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":839,\"outFeatures\":648}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":648,\"outFeatures\":28}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1333-dim input: encode down to a 131-dim bottleneck and decode back to 1333. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-3011\nComponents:\n - input (input) params={\"shape\":[1,1333]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1333]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1333,\"outFeatures\":372}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":372,\"outFeatures\":131}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":131,\"outFeatures\":372}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":372,\"outFeatures\":1333}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x31x31 image with 91 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-3012\nComponents:\n - input (input) params={\"shape\":[1,3,31,31]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,31,31]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":9,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":9,\"outChannels\":10,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":10,\"outChannels\":18,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":18,\"outChannels\":54,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":54,\"outFeatures\":91}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 491-token sequences with 32 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-3013\nComponents:\n - input (input) params={\"shape\":[1,491]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,491]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":41436,\"embeddingDim\":76}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":76,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":76,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":76,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":76,\"outFeatures\":32}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 512-token sequences with 32 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-3014\nComponents:\n - input (input) params={\"shape\":[1,512]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,512]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":19801,\"embeddingDim\":176}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":176,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[176]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":176,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[176]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":176,\"outFeatures\":32}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 2368-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-3016\nComponents:\n - input (input) params={\"shape\":[1,206]}\n - fc1 (linear) params={\"inFeatures\":206,\"outFeatures\":2368}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2368,\"outFeatures\":2368}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2368,\"outFeatures\":2368}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":2368,\"outFeatures\":2368}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":2368,\"outFeatures\":50}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":206,\"outFeatures\":129}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":129,\"outFeatures\":129}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":129,\"outFeatures\":129}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":129,\"outFeatures\":129}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":129,\"outFeatures\":50}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 46-feature, 59-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-3017\nComponents:\n - input (input) params={\"shape\":[1,46]}\n - fc1 (linear) params={\"inFeatures\":46,\"outFeatures\":232}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":232,\"outFeatures\":451}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":451,\"outFeatures\":511}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":511,\"outFeatures\":469}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":469,\"outFeatures\":59}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":232}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":451}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":511}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":469}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 55-feature user input and a 82-feature item input, each through its own 2-layer MLP tower ending at width 53, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-3018\nComponents:\n - user_input (input) params={\"shape\":[1,55]}\n - item_input (input) params={\"shape\":[1,82]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,55]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,82]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":55,\"outFeatures\":53}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":53,\"outFeatures\":53}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":82,\"outFeatures\":53}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":53,\"outFeatures\":53}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":106,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (84-feature input, 37 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-3019\nComponents:\n - input (input) params={\"shape\":[1,84]}\n - fc1 (linear) params={\"inFeatures\":84,\"outFeatures\":14}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":14,\"outFeatures\":14}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":14,\"outFeatures\":37}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":84,\"outFeatures\":696}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":696,\"outFeatures\":696}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":696,\"outFeatures\":37}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 413-feature input with 172 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-3020\nComponents:\n - input (input) params={\"shape\":[1,413]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,413]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":413,\"outFeatures\":435}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":435,\"outFeatures\":508}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":508,\"outFeatures\":202}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":202,\"outFeatures\":666}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":666,\"outFeatures\":172}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1040-dim input: encode down to a 90-dim bottleneck and decode back to 1040. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-3021\nComponents:\n - input (input) params={\"shape\":[1,1040]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1040]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1040,\"outFeatures\":97}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":97,\"outFeatures\":90}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":90,\"outFeatures\":97}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":97,\"outFeatures\":1040}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x56x56 image with 29 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-3022\nComponents:\n - input (input) params={\"shape\":[1,3,56,56]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,56,56]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":40,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":40,\"outChannels\":27,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":27,\"outChannels\":29,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":29,\"outFeatures\":29}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 157-token sequences with 56 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-3023\nComponents:\n - input (input) params={\"shape\":[1,157]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,157]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":27863,\"embeddingDim\":104}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":104,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":104,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":104,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":104,\"outFeatures\":56}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 419-token sequences with 65 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-3024\nComponents:\n - input (input) params={\"shape\":[1,419]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,419]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":22482,\"embeddingDim\":172}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":172,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[172]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":172,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[172]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":172,\"outFeatures\":65}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (300) is not divisible by numHeads (7). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-3025\nComponents:\n - input (input) params={\"shape\":[1,166]}\n - embed (embedding) params={\"numEmbeddings\":31769,\"embeddingDim\":300}\n - attn (multiHeadAttention) params={\"embedDim\":300,\"numHeads\":7}\n - head (linear) params={\"inFeatures\":300,\"outFeatures\":14}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":4}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 3021-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-3026\nComponents:\n - input (input) params={\"shape\":[1,256]}\n - fc1 (linear) params={\"inFeatures\":256,\"outFeatures\":3021}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3021,\"outFeatures\":3021}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3021,\"outFeatures\":3021}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":3021,\"outFeatures\":40}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":256,\"outFeatures\":163}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":163,\"outFeatures\":163}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":163,\"outFeatures\":163}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":163,\"outFeatures\":40}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 209-feature, 55-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-3027\nComponents:\n - input (input) params={\"shape\":[1,209]}\n - fc1 (linear) params={\"inFeatures\":209,\"outFeatures\":365}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":365,\"outFeatures\":162}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":162,\"outFeatures\":360}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":360,\"outFeatures\":482}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":482,\"outFeatures\":55}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":365}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":162}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":360}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":482}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 205-feature user input and a 252-feature item input, each through its own 2-layer MLP tower ending at width 288, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-3028\nComponents:\n - user_input (input) params={\"shape\":[1,205]}\n - item_input (input) params={\"shape\":[1,252]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,205]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,252]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":205,\"outFeatures\":288}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":288,\"outFeatures\":288}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":252,\"outFeatures\":288}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":288,\"outFeatures\":288}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":576,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (110-feature input, 29 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-3029\nComponents:\n - input (input) params={\"shape\":[1,110]}\n - fc1 (linear) params={\"inFeatures\":110,\"outFeatures\":17}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":17,\"outFeatures\":17}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":17,\"outFeatures\":29}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":110,\"outFeatures\":957}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":957,\"outFeatures\":957}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":957,\"outFeatures\":29}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 251-feature input with 21 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-3030\nComponents:\n - input (input) params={\"shape\":[1,251]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,251]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":251,\"outFeatures\":901}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":901,\"outFeatures\":132}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":132,\"outFeatures\":211}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":211,\"outFeatures\":329}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":329,\"outFeatures\":21}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1573-dim input: encode down to a 164-dim bottleneck and decode back to 1573. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-3031\nComponents:\n - input (input) params={\"shape\":[1,1573]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1573]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1573,\"outFeatures\":313}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":313,\"outFeatures\":164}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":164,\"outFeatures\":313}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":313,\"outFeatures\":1573}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x33x33 image with 11 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-3032\nComponents:\n - input (input) params={\"shape\":[1,3,33,33]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,33,33]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":39,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":39,\"outChannels\":57,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":57,\"outChannels\":42,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":42,\"outChannels\":40,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":40,\"outFeatures\":11}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 293-token sequences with 26 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-3033\nComponents:\n - input (input) params={\"shape\":[1,293]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,293]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":15562,\"embeddingDim\":144}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":144,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":144,\"outFeatures\":26}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 340-token sequences with 21 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-3034\nComponents:\n - input (input) params={\"shape\":[1,340]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,340]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":16556,\"embeddingDim\":176}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":176,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[176]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":176,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[176]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":176,\"outFeatures\":21}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 1874-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-3036\nComponents:\n - input (input) params={\"shape\":[1,172]}\n - fc1 (linear) params={\"inFeatures\":172,\"outFeatures\":1874}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":1874,\"outFeatures\":1874}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":1874,\"outFeatures\":8}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":172,\"outFeatures\":236}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":236,\"outFeatures\":236}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":236,\"outFeatures\":8}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 70-feature, 13-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-3037\nComponents:\n - input (input) params={\"shape\":[1,70]}\n - fc1 (linear) params={\"inFeatures\":70,\"outFeatures\":280}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":280,\"outFeatures\":111}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":111,\"outFeatures\":302}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":302,\"outFeatures\":13}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":280}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":111}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":302}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 110-feature user input and a 124-feature item input, each through its own 2-layer MLP tower ending at width 217, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-3038\nComponents:\n - user_input (input) params={\"shape\":[1,110]}\n - item_input (input) params={\"shape\":[1,124]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,110]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,124]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":110,\"outFeatures\":217}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":217,\"outFeatures\":217}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":124,\"outFeatures\":217}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":217,\"outFeatures\":217}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":434,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (51-feature input, 21 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-3039\nComponents:\n - input (input) params={\"shape\":[1,51]}\n - fc1 (linear) params={\"inFeatures\":51,\"outFeatures\":17}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":17,\"outFeatures\":17}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":17,\"outFeatures\":21}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":51,\"outFeatures\":1022}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1022,\"outFeatures\":1022}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1022,\"outFeatures\":21}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 157-feature input with 128 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-3040\nComponents:\n - input (input) params={\"shape\":[1,157]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,157]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":157,\"outFeatures\":346}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":346,\"outFeatures\":451}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":451,\"outFeatures\":675}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":675,\"outFeatures\":128}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 339-dim input: encode down to a 106-dim bottleneck and decode back to 339. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-3041\nComponents:\n - input (input) params={\"shape\":[1,339]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,339]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":339,\"outFeatures\":554}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":554,\"outFeatures\":106}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":106,\"outFeatures\":554}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":554,\"outFeatures\":339}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x63x63 image with 34 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-3042\nComponents:\n - input (input) params={\"shape\":[1,3,63,63]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,63,63]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":55,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":55,\"outChannels\":57,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":57,\"outChannels\":27,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":27,\"outFeatures\":34}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 271-token sequences with 29 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-3043\nComponents:\n - input (input) params={\"shape\":[1,271]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,271]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":44125,\"embeddingDim\":220}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":220,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":220,\"outFeatures\":29}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 105-token sequences with 94 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-3044\nComponents:\n - input (input) params={\"shape\":[1,105]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,105]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":25427,\"embeddingDim\":768}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":768,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[768]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":768,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[768]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":768,\"numHeads\":16,\"numKVHeads\":8}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[768]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":768,\"outFeatures\":94}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3763-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-3046\nComponents:\n - input (input) params={\"shape\":[1,167]}\n - fc1 (linear) params={\"inFeatures\":167,\"outFeatures\":3763}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3763,\"outFeatures\":3763}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3763,\"outFeatures\":3763}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3763,\"outFeatures\":3763}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3763,\"outFeatures\":44}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":167,\"outFeatures\":186}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":186,\"outFeatures\":186}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":186,\"outFeatures\":186}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":186,\"outFeatures\":186}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":186,\"outFeatures\":44}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 22-feature, 59-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-3047\nComponents:\n - input (input) params={\"shape\":[1,22]}\n - fc1 (linear) params={\"inFeatures\":22,\"outFeatures\":69}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":69,\"outFeatures\":218}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":218,\"outFeatures\":332}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":332,\"outFeatures\":145}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":145,\"outFeatures\":497}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":497,\"outFeatures\":59}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":69}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":218}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":332}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":145}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":497}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 119-feature user input and a 52-feature item input, each through its own 2-layer MLP tower ending at width 42, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-3048\nComponents:\n - user_input (input) params={\"shape\":[1,119]}\n - item_input (input) params={\"shape\":[1,52]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,119]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,52]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":119,\"outFeatures\":42}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":42,\"outFeatures\":42}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":52,\"outFeatures\":42}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":42,\"outFeatures\":42}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":84,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (94-feature input, 4 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-3049\nComponents:\n - input (input) params={\"shape\":[1,94]}\n - fc1 (linear) params={\"inFeatures\":94,\"outFeatures\":19}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":19,\"outFeatures\":19}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":19,\"outFeatures\":4}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":94,\"outFeatures\":1022}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1022,\"outFeatures\":1022}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1022,\"outFeatures\":4}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 209-feature input with 149 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-3050\nComponents:\n - input (input) params={\"shape\":[1,209]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,209]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":209,\"outFeatures\":184}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":184,\"outFeatures\":953}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":953,\"outFeatures\":149}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1958-dim input: encode down to a 206-dim bottleneck and decode back to 1958. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-3051\nComponents:\n - input (input) params={\"shape\":[1,1958]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1958]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1958,\"outFeatures\":564}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":564,\"outFeatures\":206}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":206,\"outFeatures\":564}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":564,\"outFeatures\":1958}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x63x63 image with 75 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-3052\nComponents:\n - input (input) params={\"shape\":[1,3,63,63]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,63,63]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":55,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":55,\"outChannels\":44,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":44,\"outChannels\":47,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":47,\"outChannels\":18,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":18,\"outFeatures\":75}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 398-token sequences with 41 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-3053\nComponents:\n - input (input) params={\"shape\":[1,398]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,398]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":10950,\"embeddingDim\":32}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":32,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":32,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":32,\"outFeatures\":41}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 344-token sequences with 92 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-3054\nComponents:\n - input (input) params={\"shape\":[1,344]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,344]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":14430,\"embeddingDim\":92}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":92,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[92]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":92,\"outFeatures\":92}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3523-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-3056\nComponents:\n - input (input) params={\"shape\":[1,225]}\n - fc1 (linear) params={\"inFeatures\":225,\"outFeatures\":3523}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3523,\"outFeatures\":3523}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3523,\"outFeatures\":3523}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3523,\"outFeatures\":3523}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3523,\"outFeatures\":19}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":225,\"outFeatures\":346}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":346,\"outFeatures\":346}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":346,\"outFeatures\":346}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":346,\"outFeatures\":346}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":346,\"outFeatures\":19}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 220-feature, 32-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-3057\nComponents:\n - input (input) params={\"shape\":[1,220]}\n - fc1 (linear) params={\"inFeatures\":220,\"outFeatures\":396}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":396,\"outFeatures\":217}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":217,\"outFeatures\":473}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":473,\"outFeatures\":32}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":396}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":217}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":473}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 222-feature user input and a 77-feature item input, each through its own 2-layer MLP tower ending at width 151, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-3058\nComponents:\n - user_input (input) params={\"shape\":[1,222]}\n - item_input (input) params={\"shape\":[1,77]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,222]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,77]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":222,\"outFeatures\":151}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":151,\"outFeatures\":151}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":77,\"outFeatures\":151}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":151,\"outFeatures\":151}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":302,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (46-feature input, 45 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-3059\nComponents:\n - input (input) params={\"shape\":[1,46]}\n - fc1 (linear) params={\"inFeatures\":46,\"outFeatures\":6}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":6,\"outFeatures\":6}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":6,\"outFeatures\":45}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":46,\"outFeatures\":673}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":673,\"outFeatures\":673}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":673,\"outFeatures\":45}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 167-feature input with 132 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-3060\nComponents:\n - input (input) params={\"shape\":[1,167]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,167]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":167,\"outFeatures\":879}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":879,\"outFeatures\":484}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":484,\"outFeatures\":194}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":194,\"outFeatures\":451}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":451,\"outFeatures\":269}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":269,\"outFeatures\":25}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":25,\"outFeatures\":132}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 679-dim input: encode down to a 71-dim bottleneck and decode back to 679. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-3061\nComponents:\n - input (input) params={\"shape\":[1,679]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,679]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":679,\"outFeatures\":329}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":329,\"outFeatures\":71}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":71,\"outFeatures\":329}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":329,\"outFeatures\":679}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x29x29 image with 55 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-3062\nComponents:\n - input (input) params={\"shape\":[1,3,29,29]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,29,29]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":57,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":57,\"outChannels\":41,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":41,\"outChannels\":62,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":62,\"outFeatures\":55}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 470-token sequences with 42 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-3063\nComponents:\n - input (input) params={\"shape\":[1,470]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,470]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":24690,\"embeddingDim\":416}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":416,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":416,\"outFeatures\":42}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 472-token sequences with 56 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-3064\nComponents:\n - input (input) params={\"shape\":[1,472]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,472]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":22610,\"embeddingDim\":44}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":44,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[44]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":44,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[44]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":44,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[44]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":44,\"outFeatures\":56}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 2394-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-3066\nComponents:\n - input (input) params={\"shape\":[1,43]}\n - fc1 (linear) params={\"inFeatures\":43,\"outFeatures\":2394}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2394,\"outFeatures\":2394}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":2394,\"outFeatures\":46}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":43,\"outFeatures\":70}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":70,\"outFeatures\":70}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":70,\"outFeatures\":46}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 95-feature, 18-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-3067\nComponents:\n - input (input) params={\"shape\":[1,95]}\n - fc1 (linear) params={\"inFeatures\":95,\"outFeatures\":461}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":461,\"outFeatures\":170}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":170,\"outFeatures\":366}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":366,\"outFeatures\":152}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":152,\"outFeatures\":18}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":461}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":170}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":366}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":152}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 255-feature user input and a 60-feature item input, each through its own 2-layer MLP tower ending at width 426, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-3068\nComponents:\n - user_input (input) params={\"shape\":[1,255]}\n - item_input (input) params={\"shape\":[1,60]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,255]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,60]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":255,\"outFeatures\":426}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":426,\"outFeatures\":426}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":60,\"outFeatures\":426}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":426,\"outFeatures\":426}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":852,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (54-feature input, 37 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-3069\nComponents:\n - input (input) params={\"shape\":[1,54]}\n - fc1 (linear) params={\"inFeatures\":54,\"outFeatures\":21}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":21,\"outFeatures\":21}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":21,\"outFeatures\":37}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":54,\"outFeatures\":1258}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1258,\"outFeatures\":1258}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1258,\"outFeatures\":37}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 116-feature input with 190 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-3070\nComponents:\n - input (input) params={\"shape\":[1,116]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,116]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":116,\"outFeatures\":965}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":965,\"outFeatures\":236}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":236,\"outFeatures\":949}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":949,\"outFeatures\":190}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1529-dim input: encode down to a 212-dim bottleneck and decode back to 1529. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-3071\nComponents:\n - input (input) params={\"shape\":[1,1529]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1529]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1529,\"outFeatures\":472}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":472,\"outFeatures\":212}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":212,\"outFeatures\":472}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":472,\"outFeatures\":1529}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x56x56 image with 54 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-3072\nComponents:\n - input (input) params={\"shape\":[1,3,56,56]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,56,56]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":56,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":56,\"outChannels\":40,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":40,\"outChannels\":23,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":23,\"outFeatures\":54}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 377-token sequences with 94 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-3073\nComponents:\n - input (input) params={\"shape\":[1,377]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,377]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":35145,\"embeddingDim\":432}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":432,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":432,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":432,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":432,\"outFeatures\":94}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 308-token sequences with 74 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-3074\nComponents:\n - input (input) params={\"shape\":[1,308]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,308]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":29550,\"embeddingDim\":256}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":256,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[256]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":256,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[256]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":256,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[256]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":256,\"outFeatures\":74}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 2006-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-3076\nComponents:\n - input (input) params={\"shape\":[1,142]}\n - fc1 (linear) params={\"inFeatures\":142,\"outFeatures\":2006}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2006,\"outFeatures\":2006}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":2006,\"outFeatures\":48}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":142,\"outFeatures\":91}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":91,\"outFeatures\":91}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":91,\"outFeatures\":48}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 139-feature, 20-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-3077\nComponents:\n - input (input) params={\"shape\":[1,139]}\n - fc1 (linear) params={\"inFeatures\":139,\"outFeatures\":429}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":429,\"outFeatures\":323}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":323,\"outFeatures\":20}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":429}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":323}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 99-feature user input and a 157-feature item input, each through its own 2-layer MLP tower ending at width 414, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-3078\nComponents:\n - user_input (input) params={\"shape\":[1,99]}\n - item_input (input) params={\"shape\":[1,157]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,99]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,157]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":99,\"outFeatures\":414}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":414,\"outFeatures\":414}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":157,\"outFeatures\":414}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":414,\"outFeatures\":414}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":828,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (108-feature input, 19 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-3079\nComponents:\n - input (input) params={\"shape\":[1,108]}\n - fc1 (linear) params={\"inFeatures\":108,\"outFeatures\":6}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":6,\"outFeatures\":6}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":6,\"outFeatures\":19}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":108,\"outFeatures\":1214}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1214,\"outFeatures\":1214}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1214,\"outFeatures\":19}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 115-feature input with 37 output classes. Use 2 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-3080\nComponents:\n - input (input) params={\"shape\":[1,115]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,115]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":115,\"outFeatures\":544}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":544,\"outFeatures\":123}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":123,\"outFeatures\":37}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 751-dim input: encode down to a 31-dim bottleneck and decode back to 751. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-3081\nComponents:\n - input (input) params={\"shape\":[1,751]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,751]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":751,\"outFeatures\":726}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":726,\"outFeatures\":31}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":31,\"outFeatures\":726}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":726,\"outFeatures\":751}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x51x51 image with 25 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-3082\nComponents:\n - input (input) params={\"shape\":[1,3,51,51]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,51,51]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":36,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":36,\"outChannels\":64,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":64,\"outChannels\":20,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":20,\"outChannels\":31,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":31,\"outFeatures\":25}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 202-token sequences with 16 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-3083\nComponents:\n - input (input) params={\"shape\":[1,202]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,202]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":47775,\"embeddingDim\":40}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":40,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":40,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":40,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":40,\"outFeatures\":16}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 311-token sequences with 38 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-3084\nComponents:\n - input (input) params={\"shape\":[1,311]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,311]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":8169,\"embeddingDim\":92}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":92,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[92]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":92,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[92]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":92,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[92]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":92,\"outFeatures\":38}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 1681-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-3086\nComponents:\n - input (input) params={\"shape\":[1,225]}\n - fc1 (linear) params={\"inFeatures\":225,\"outFeatures\":1681}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":1681,\"outFeatures\":1681}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":1681,\"outFeatures\":1681}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":1681,\"outFeatures\":1681}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":1681,\"outFeatures\":47}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":225,\"outFeatures\":89}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":89,\"outFeatures\":89}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":89,\"outFeatures\":89}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":89,\"outFeatures\":89}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":89,\"outFeatures\":47}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 46-feature, 5-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-3087\nComponents:\n - input (input) params={\"shape\":[1,46]}\n - fc1 (linear) params={\"inFeatures\":46,\"outFeatures\":459}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":459,\"outFeatures\":377}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":377,\"outFeatures\":273}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":273,\"outFeatures\":184}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":184,\"outFeatures\":191}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":191,\"outFeatures\":5}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":459}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":377}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":273}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":184}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":191}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 113-feature user input and a 29-feature item input, each through its own 2-layer MLP tower ending at width 432, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-3088\nComponents:\n - user_input (input) params={\"shape\":[1,113]}\n - item_input (input) params={\"shape\":[1,29]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,113]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,29]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":113,\"outFeatures\":432}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":432,\"outFeatures\":432}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":29,\"outFeatures\":432}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":432,\"outFeatures\":432}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":864,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (111-feature input, 37 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-3089\nComponents:\n - input (input) params={\"shape\":[1,111]}\n - fc1 (linear) params={\"inFeatures\":111,\"outFeatures\":9}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":9,\"outFeatures\":9}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":9,\"outFeatures\":37}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":111,\"outFeatures\":1052}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1052,\"outFeatures\":1052}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1052,\"outFeatures\":37}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 94-feature input with 35 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-3090\nComponents:\n - input (input) params={\"shape\":[1,94]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,94]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":94,\"outFeatures\":303}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":303,\"outFeatures\":562}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":562,\"outFeatures\":454}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":454,\"outFeatures\":124}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":124,\"outFeatures\":217}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":217,\"outFeatures\":581}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":581,\"outFeatures\":35}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 2014-dim input: encode down to a 174-dim bottleneck and decode back to 2014. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-3091\nComponents:\n - input (input) params={\"shape\":[1,2014]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,2014]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":2014,\"outFeatures\":699}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":699,\"outFeatures\":174}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":174,\"outFeatures\":699}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":699,\"outFeatures\":2014}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x29x29 image with 67 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-3092\nComponents:\n - input (input) params={\"shape\":[1,3,29,29]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,29,29]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":46,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":46,\"outChannels\":9,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":9,\"outFeatures\":67}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 366-token sequences with 82 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-3093\nComponents:\n - input (input) params={\"shape\":[1,366]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,366]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":21856,\"embeddingDim\":152}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":152,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":152,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":152,\"outFeatures\":82}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 227-token sequences with 57 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-3094\nComponents:\n - input (input) params={\"shape\":[1,227]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,227]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":26367,\"embeddingDim\":360}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":360,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[360]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":360,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[360]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":360,\"outFeatures\":57}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 2657-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-3096\nComponents:\n - input (input) params={\"shape\":[1,46]}\n - fc1 (linear) params={\"inFeatures\":46,\"outFeatures\":2657}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2657,\"outFeatures\":2657}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2657,\"outFeatures\":2657}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":2657,\"outFeatures\":30}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":46,\"outFeatures\":239}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":239,\"outFeatures\":239}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":239,\"outFeatures\":239}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":239,\"outFeatures\":30}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 159-feature, 32-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-3097\nComponents:\n - input (input) params={\"shape\":[1,159]}\n - fc1 (linear) params={\"inFeatures\":159,\"outFeatures\":143}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":143,\"outFeatures\":474}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":474,\"outFeatures\":511}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":511,\"outFeatures\":32}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":143}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":474}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":511}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 201-feature user input and a 254-feature item input, each through its own 2-layer MLP tower ending at width 443, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-3098\nComponents:\n - user_input (input) params={\"shape\":[1,201]}\n - item_input (input) params={\"shape\":[1,254]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,201]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,254]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":201,\"outFeatures\":443}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":443,\"outFeatures\":443}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":254,\"outFeatures\":443}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":443,\"outFeatures\":443}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":886,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (110-feature input, 36 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-3099\nComponents:\n - input (input) params={\"shape\":[1,110]}\n - fc1 (linear) params={\"inFeatures\":110,\"outFeatures\":6}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":6,\"outFeatures\":6}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":6,\"outFeatures\":36}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":110,\"outFeatures\":643}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":643,\"outFeatures\":643}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":643,\"outFeatures\":36}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 419-feature input with 160 output classes. Use 4 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-3100\nComponents:\n - input (input) params={\"shape\":[1,419]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,419]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":419,\"outFeatures\":367}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":367,\"outFeatures\":584}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":584,\"outFeatures\":230}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":230,\"outFeatures\":278}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":278,\"outFeatures\":160}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 338-dim input: encode down to a 190-dim bottleneck and decode back to 338. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-3101\nComponents:\n - input (input) params={\"shape\":[1,338]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,338]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":338,\"outFeatures\":105}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":105,\"outFeatures\":190}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":190,\"outFeatures\":105}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":105,\"outFeatures\":338}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x29x29 image with 6 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-3102\nComponents:\n - input (input) params={\"shape\":[1,3,29,29]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,29,29]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":13,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":13,\"outChannels\":20,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":20,\"outChannels\":38,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":38,\"outChannels\":61,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":61,\"outFeatures\":6}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 197-token sequences with 75 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-3103\nComponents:\n - input (input) params={\"shape\":[1,197]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,197]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":30098,\"embeddingDim\":144}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":144,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":144,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":144,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":144,\"outFeatures\":75}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 57-token sequences with 68 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-3104\nComponents:\n - input (input) params={\"shape\":[1,57]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,57]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":49247,\"embeddingDim\":560}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":560,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[560]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":560,\"numHeads\":16,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[560]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":560,\"outFeatures\":68}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (468) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-3105\nComponents:\n - input (input) params={\"shape\":[1,307]}\n - embed (embedding) params={\"numEmbeddings\":37364,\"embeddingDim\":468}\n - attn (multiHeadAttention) params={\"embedDim\":468,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":468,\"outFeatures\":18}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":4}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3265-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-3106\nComponents:\n - input (input) params={\"shape\":[1,178]}\n - fc1 (linear) params={\"inFeatures\":178,\"outFeatures\":3265}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3265,\"outFeatures\":3265}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3265,\"outFeatures\":3265}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3265,\"outFeatures\":3265}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3265,\"outFeatures\":42}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":178,\"outFeatures\":148}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":148,\"outFeatures\":148}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":148,\"outFeatures\":148}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":148,\"outFeatures\":148}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":148,\"outFeatures\":42}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 237-feature, 69-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-3107\nComponents:\n - input (input) params={\"shape\":[1,237]}\n - fc1 (linear) params={\"inFeatures\":237,\"outFeatures\":321}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":321,\"outFeatures\":341}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":341,\"outFeatures\":114}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":114,\"outFeatures\":303}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":303,\"outFeatures\":69}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":321}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":341}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":114}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":303}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 204-feature user input and a 239-feature item input, each through its own 2-layer MLP tower ending at width 461, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-3108\nComponents:\n - user_input (input) params={\"shape\":[1,204]}\n - item_input (input) params={\"shape\":[1,239]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,204]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,239]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":204,\"outFeatures\":461}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":461,\"outFeatures\":461}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":239,\"outFeatures\":461}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":461,\"outFeatures\":461}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":922,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (103-feature input, 45 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-3109\nComponents:\n - input (input) params={\"shape\":[1,103]}\n - fc1 (linear) params={\"inFeatures\":103,\"outFeatures\":10}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":10,\"outFeatures\":10}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":10,\"outFeatures\":45}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":103,\"outFeatures\":711}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":711,\"outFeatures\":711}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":711,\"outFeatures\":45}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 426-feature input with 105 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-3110\nComponents:\n - input (input) params={\"shape\":[1,426]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,426]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":426,\"outFeatures\":874}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":874,\"outFeatures\":582}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":582,\"outFeatures\":827}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":827,\"outFeatures\":289}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":289,\"outFeatures\":514}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":514,\"outFeatures\":105}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 464-dim input: encode down to a 110-dim bottleneck and decode back to 464. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-3111\nComponents:\n - input (input) params={\"shape\":[1,464]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,464]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":464,\"outFeatures\":715}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":715,\"outFeatures\":110}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":110,\"outFeatures\":715}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":715,\"outFeatures\":464}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x58x58 image with 49 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-3112\nComponents:\n - input (input) params={\"shape\":[1,3,58,58]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,58,58]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":60,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":60,\"outChannels\":51,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":51,\"outChannels\":12,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":12,\"outFeatures\":49}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 460-token sequences with 85 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-3113\nComponents:\n - input (input) params={\"shape\":[1,460]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,460]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":28681,\"embeddingDim\":236}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":236,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":236,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":236,\"outFeatures\":85}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 474-token sequences with 25 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-3114\nComponents:\n - input (input) params={\"shape\":[1,474]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,474]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":48997,\"embeddingDim\":104}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":104,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[104]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":104,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[104]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":104,\"outFeatures\":25}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 3672-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-3116\nComponents:\n - input (input) params={\"shape\":[1,157]}\n - fc1 (linear) params={\"inFeatures\":157,\"outFeatures\":3672}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3672,\"outFeatures\":3672}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":3672,\"outFeatures\":24}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":157,\"outFeatures\":110}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":110,\"outFeatures\":110}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":110,\"outFeatures\":24}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 75-feature, 47-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-3117\nComponents:\n - input (input) params={\"shape\":[1,75]}\n - fc1 (linear) params={\"inFeatures\":75,\"outFeatures\":410}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":410,\"outFeatures\":51}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":51,\"outFeatures\":336}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":336,\"outFeatures\":305}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":305,\"outFeatures\":169}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":169,\"outFeatures\":47}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":410}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":51}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":336}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":305}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":169}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 59-feature user input and a 81-feature item input, each through its own 2-layer MLP tower ending at width 219, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-3118\nComponents:\n - user_input (input) params={\"shape\":[1,59]}\n - item_input (input) params={\"shape\":[1,81]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,59]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,81]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":59,\"outFeatures\":219}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":219,\"outFeatures\":219}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":81,\"outFeatures\":219}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":219,\"outFeatures\":219}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":438,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (32-feature input, 16 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-3119\nComponents:\n - input (input) params={\"shape\":[1,32]}\n - fc1 (linear) params={\"inFeatures\":32,\"outFeatures\":20}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":20,\"outFeatures\":20}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":20,\"outFeatures\":16}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":32,\"outFeatures\":839}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":839,\"outFeatures\":839}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":839,\"outFeatures\":16}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 19-feature input with 9 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-3120\nComponents:\n - input (input) params={\"shape\":[1,19]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,19]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":19,\"outFeatures\":847}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":847,\"outFeatures\":93}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":93,\"outFeatures\":486}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":486,\"outFeatures\":297}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":297,\"outFeatures\":363}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":363,\"outFeatures\":9}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1195-dim input: encode down to a 169-dim bottleneck and decode back to 1195. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-3121\nComponents:\n - input (input) params={\"shape\":[1,1195]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1195]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1195,\"outFeatures\":230}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":230,\"outFeatures\":169}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":169,\"outFeatures\":230}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":230,\"outFeatures\":1195}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x24x24 image with 70 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-3122\nComponents:\n - input (input) params={\"shape\":[1,3,24,24]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,24,24]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":14,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":14,\"outChannels\":51,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":51,\"outChannels\":60,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":60,\"outChannels\":9,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":9,\"outFeatures\":70}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 372-token sequences with 44 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-3123\nComponents:\n - input (input) params={\"shape\":[1,372]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,372]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":13764,\"embeddingDim\":70}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":70,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":70,\"outFeatures\":44}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 34-token sequences with 18 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-3124\nComponents:\n - input (input) params={\"shape\":[1,34]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,34]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":9200,\"embeddingDim\":344}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":344,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[344]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":344,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[344]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":344,\"outFeatures\":18}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 3221-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-3126\nComponents:\n - input (input) params={\"shape\":[1,166]}\n - fc1 (linear) params={\"inFeatures\":166,\"outFeatures\":3221}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3221,\"outFeatures\":3221}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3221,\"outFeatures\":3221}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":3221,\"outFeatures\":36}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":166,\"outFeatures\":370}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":370,\"outFeatures\":370}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":370,\"outFeatures\":370}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":370,\"outFeatures\":36}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 148-feature, 89-class MLP trains unstably. Insert a batchNorm1d after each of the 2 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-3127\nComponents:\n - input (input) params={\"shape\":[1,148]}\n - fc1 (linear) params={\"inFeatures\":148,\"outFeatures\":144}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":144,\"outFeatures\":185}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":185,\"outFeatures\":89}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":144}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":185}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 207-feature user input and a 136-feature item input, each through its own 2-layer MLP tower ending at width 62, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-3128\nComponents:\n - user_input (input) params={\"shape\":[1,207]}\n - item_input (input) params={\"shape\":[1,136]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,207]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,136]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":207,\"outFeatures\":62}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":62,\"outFeatures\":62}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":136,\"outFeatures\":62}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":62,\"outFeatures\":62}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":124,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (59-feature input, 49 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-3129\nComponents:\n - input (input) params={\"shape\":[1,59]}\n - fc1 (linear) params={\"inFeatures\":59,\"outFeatures\":12}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":12,\"outFeatures\":12}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":12,\"outFeatures\":49}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":59,\"outFeatures\":939}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":939,\"outFeatures\":939}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":939,\"outFeatures\":49}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 51-feature input with 72 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-3130\nComponents:\n - input (input) params={\"shape\":[1,51]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,51]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":51,\"outFeatures\":941}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":941,\"outFeatures\":756}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":756,\"outFeatures\":759}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":759,\"outFeatures\":368}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":368,\"outFeatures\":48}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":48,\"outFeatures\":72}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 512-dim input: encode down to a 118-dim bottleneck and decode back to 512. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-3131\nComponents:\n - input (input) params={\"shape\":[1,512]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,512]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":512,\"outFeatures\":114}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":114,\"outFeatures\":118}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":118,\"outFeatures\":114}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":114,\"outFeatures\":512}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x30x30 image with 11 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-3132\nComponents:\n - input (input) params={\"shape\":[1,3,30,30]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,30,30]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":62,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":62,\"outChannels\":17,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":17,\"outFeatures\":11}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 342-token sequences with 93 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-3133\nComponents:\n - input (input) params={\"shape\":[1,342]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,342]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":24448,\"embeddingDim\":92}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":92,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":92,\"outFeatures\":93}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 34-token sequences with 74 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-3134\nComponents:\n - input (input) params={\"shape\":[1,34]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,34]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":20083,\"embeddingDim\":96}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":96,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[96]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":96,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[96]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":96,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[96]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":96,\"outFeatures\":74}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 3-hidden-layer MLP uses 3163-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 3 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-3136\nComponents:\n - input (input) params={\"shape\":[1,201]}\n - fc1 (linear) params={\"inFeatures\":201,\"outFeatures\":3163}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3163,\"outFeatures\":3163}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3163,\"outFeatures\":3163}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":3163,\"outFeatures\":24}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":201,\"outFeatures\":255}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":255,\"outFeatures\":255}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":255,\"outFeatures\":255}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":255,\"outFeatures\":24}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 78-feature, 63-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-3137\nComponents:\n - input (input) params={\"shape\":[1,78]}\n - fc1 (linear) params={\"inFeatures\":78,\"outFeatures\":237}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":237,\"outFeatures\":318}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":318,\"outFeatures\":475}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":475,\"outFeatures\":63}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":237}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":318}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":475}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 102-feature user input and a 134-feature item input, each through its own 2-layer MLP tower ending at width 213, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-3138\nComponents:\n - user_input (input) params={\"shape\":[1,102]}\n - item_input (input) params={\"shape\":[1,134]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,102]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,134]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":102,\"outFeatures\":213}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":213,\"outFeatures\":213}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":134,\"outFeatures\":213}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":213,\"outFeatures\":213}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":426,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (42-feature input, 41 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-3139\nComponents:\n - input (input) params={\"shape\":[1,42]}\n - fc1 (linear) params={\"inFeatures\":42,\"outFeatures\":9}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":9,\"outFeatures\":9}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":9,\"outFeatures\":41}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":42,\"outFeatures\":1163}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1163,\"outFeatures\":1163}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1163,\"outFeatures\":41}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 201-feature input with 126 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-3140\nComponents:\n - input (input) params={\"shape\":[1,201]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,201]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":201,\"outFeatures\":399}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":399,\"outFeatures\":307}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":307,\"outFeatures\":965}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":965,\"outFeatures\":126}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 999-dim input: encode down to a 116-dim bottleneck and decode back to 999. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-3141\nComponents:\n - input (input) params={\"shape\":[1,999]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,999]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":999,\"outFeatures\":700}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":700,\"outFeatures\":116}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":116,\"outFeatures\":700}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":700,\"outFeatures\":999}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x47x47 image with 48 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-3142\nComponents:\n - input (input) params={\"shape\":[1,3,47,47]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,47,47]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":58,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":58,\"outChannels\":49,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":49,\"outChannels\":9,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":9,\"outFeatures\":48}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 312-token sequences with 62 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-3143\nComponents:\n - input (input) params={\"shape\":[1,312]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,312]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":46513,\"embeddingDim\":156}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":156,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":156,\"outFeatures\":62}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 230-token sequences with 72 output classes: token embedding, 1 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-3144\nComponents:\n - input (input) params={\"shape\":[1,230]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,230]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":22722,\"embeddingDim\":48}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":48,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[48]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":48,\"outFeatures\":72}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (220) is not divisible by numHeads (7). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-3145\nComponents:\n - input (input) params={\"shape\":[1,89]}\n - embed (embedding) params={\"numEmbeddings\":9183,\"embeddingDim\":220}\n - attn (multiHeadAttention) params={\"embedDim\":220,\"numHeads\":7}\n - head (linear) params={\"inFeatures\":220,\"outFeatures\":80}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":4}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 1670-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-3146\nComponents:\n - input (input) params={\"shape\":[1,97]}\n - fc1 (linear) params={\"inFeatures\":97,\"outFeatures\":1670}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":1670,\"outFeatures\":1670}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":1670,\"outFeatures\":1670}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":1670,\"outFeatures\":1670}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":1670,\"outFeatures\":19}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":97,\"outFeatures\":263}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":263,\"outFeatures\":263}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":263,\"outFeatures\":263}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":263,\"outFeatures\":263}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":263,\"outFeatures\":19}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 39-feature, 5-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-3147\nComponents:\n - input (input) params={\"shape\":[1,39]}\n - fc1 (linear) params={\"inFeatures\":39,\"outFeatures\":310}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":310,\"outFeatures\":394}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":394,\"outFeatures\":71}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":71,\"outFeatures\":457}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":457,\"outFeatures\":5}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":310}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":394}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":71}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":457}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 109-feature user input and a 100-feature item input, each through its own 2-layer MLP tower ending at width 277, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-3148\nComponents:\n - user_input (input) params={\"shape\":[1,109]}\n - item_input (input) params={\"shape\":[1,100]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,109]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,100]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":109,\"outFeatures\":277}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":277,\"outFeatures\":277}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":100,\"outFeatures\":277}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":277,\"outFeatures\":277}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":554,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (64-feature input, 18 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-3149\nComponents:\n - input (input) params={\"shape\":[1,64]}\n - fc1 (linear) params={\"inFeatures\":64,\"outFeatures\":10}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":10,\"outFeatures\":10}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":10,\"outFeatures\":18}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":64,\"outFeatures\":1135}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1135,\"outFeatures\":1135}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1135,\"outFeatures\":18}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 90-feature input with 186 output classes. Use 3 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-3150\nComponents:\n - input (input) params={\"shape\":[1,90]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,90]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":90,\"outFeatures\":181}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":181,\"outFeatures\":655}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":655,\"outFeatures\":330}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":330,\"outFeatures\":186}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1908-dim input: encode down to a 18-dim bottleneck and decode back to 1908. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-3151\nComponents:\n - input (input) params={\"shape\":[1,1908]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1908]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1908,\"outFeatures\":183}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":183,\"outFeatures\":18}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":18,\"outFeatures\":183}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":183,\"outFeatures\":1908}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x52x52 image with 13 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-3152\nComponents:\n - input (input) params={\"shape\":[1,3,52,52]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,52,52]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":41,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":41,\"outChannels\":53,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":53,\"outFeatures\":13}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 457-token sequences with 61 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-3153\nComponents:\n - input (input) params={\"shape\":[1,457]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,457]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":43370,\"embeddingDim\":128}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":128,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":128,\"numHeads\":8}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":128,\"numHeads\":8}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":128,\"outFeatures\":61}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 53-token sequences with 37 output classes: token embedding, 3 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-3154\nComponents:\n - input (input) params={\"shape\":[1,53]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,53]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":10713,\"embeddingDim\":184}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":184,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[184]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":184,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[184]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":184,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm3\",\"params\":{\"normalizedShape\":[184]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":184,\"outFeatures\":37}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"norm3\"},{\"from\":\"norm3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (484) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-3155\nComponents:\n - input (input) params={\"shape\":[1,307]}\n - embed (embedding) params={\"numEmbeddings\":33320,\"embeddingDim\":484}\n - attn (multiHeadAttention) params={\"embedDim\":484,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":484,\"outFeatures\":33}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":4}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 2458-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-3156\nComponents:\n - input (input) params={\"shape\":[1,187]}\n - fc1 (linear) params={\"inFeatures\":187,\"outFeatures\":2458}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2458,\"outFeatures\":2458}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2458,\"outFeatures\":2458}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":2458,\"outFeatures\":2458}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":2458,\"outFeatures\":4}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":187,\"outFeatures\":135}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":135,\"outFeatures\":135}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":135,\"outFeatures\":135}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":135,\"outFeatures\":135}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":135,\"outFeatures\":4}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 94-feature, 30-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-3157\nComponents:\n - input (input) params={\"shape\":[1,94]}\n - fc1 (linear) params={\"inFeatures\":94,\"outFeatures\":451}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":451,\"outFeatures\":109}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":109,\"outFeatures\":243}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":243,\"outFeatures\":496}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":496,\"outFeatures\":30}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":451}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":109}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":243}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":496}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 219-feature user input and a 37-feature item input, each through its own 2-layer MLP tower ending at width 389, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-3158\nComponents:\n - user_input (input) params={\"shape\":[1,219]}\n - item_input (input) params={\"shape\":[1,37]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,219]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,37]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":219,\"outFeatures\":389}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":389,\"outFeatures\":389}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":37,\"outFeatures\":389}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":389,\"outFeatures\":389}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":778,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (63-feature input, 43 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-3159\nComponents:\n - input (input) params={\"shape\":[1,63]}\n - fc1 (linear) params={\"inFeatures\":63,\"outFeatures\":12}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":12,\"outFeatures\":12}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":12,\"outFeatures\":43}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":63,\"outFeatures\":1137}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":1137,\"outFeatures\":1137}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":1137,\"outFeatures\":43}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 70-feature input with 162 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-3160\nComponents:\n - input (input) params={\"shape\":[1,70]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,70]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":70,\"outFeatures\":571}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":571,\"outFeatures\":528}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":528,\"outFeatures\":100}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":100,\"outFeatures\":455}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":455,\"outFeatures\":539}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":539,\"outFeatures\":162}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 381-dim input: encode down to a 13-dim bottleneck and decode back to 381. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-3161\nComponents:\n - input (input) params={\"shape\":[1,381]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,381]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":381,\"outFeatures\":418}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":418,\"outFeatures\":13}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":13,\"outFeatures\":418}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":418,\"outFeatures\":381}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x35x35 image with 70 classes. Use 4 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-3162\nComponents:\n - input (input) params={\"shape\":[1,3,35,35]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,35,35]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":35,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":35,\"outChannels\":54,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":54,\"outChannels\":64,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv4\",\"params\":{\"inChannels\":64,\"outChannels\":47,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":47,\"outFeatures\":70}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"conv4\"},{\"from\":\"conv4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 371-token sequences with 63 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-3163\nComponents:\n - input (input) params={\"shape\":[1,371]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,371]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":31252,\"embeddingDim\":100}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":100,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":100,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":100,\"outFeatures\":63}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 459-token sequences with 94 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-3164\nComponents:\n - input (input) params={\"shape\":[1,459]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,459]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":38735,\"embeddingDim\":384}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":384,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[384]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":384,\"numHeads\":8,\"numKVHeads\":4}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[384]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":384,\"outFeatures\":94}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP uses 2320-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 2 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-3166\nComponents:\n - input (input) params={\"shape\":[1,75]}\n - fc1 (linear) params={\"inFeatures\":75,\"outFeatures\":2320}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2320,\"outFeatures\":2320}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":2320,\"outFeatures\":17}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":75,\"outFeatures\":119}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":119,\"outFeatures\":119}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":119,\"outFeatures\":17}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 111-feature, 84-class MLP trains unstably. Insert a batchNorm1d after each of the 5 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-3167\nComponents:\n - input (input) params={\"shape\":[1,111]}\n - fc1 (linear) params={\"inFeatures\":111,\"outFeatures\":237}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":237,\"outFeatures\":266}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":266,\"outFeatures\":116}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":116,\"outFeatures\":192}\n - act4 (relu)\n - fc5 (linear) params={\"inFeatures\":192,\"outFeatures\":333}\n - act5 (relu)\n - head (linear) params={\"inFeatures\":333,\"outFeatures\":84}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> fc5\n - fc5 -> act5\n - act5 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":237}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":266}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":116}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":192}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn5\",\"afterName\":\"fc5\",\"params\":{\"numFeatures\":333}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 216-feature user input and a 240-feature item input, each through its own 2-layer MLP tower ending at width 197, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-3168\nComponents:\n - user_input (input) params={\"shape\":[1,216]}\n - item_input (input) params={\"shape\":[1,240]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,216]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,240]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":216,\"outFeatures\":197}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":197,\"outFeatures\":197}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":240,\"outFeatures\":197}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":197,\"outFeatures\":197}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":394,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (20-feature input, 11 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-3169\nComponents:\n - input (input) params={\"shape\":[1,20]}\n - fc1 (linear) params={\"inFeatures\":20,\"outFeatures\":4}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":4,\"outFeatures\":4}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":4,\"outFeatures\":11}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":20,\"outFeatures\":963}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":963,\"outFeatures\":963}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":963,\"outFeatures\":11}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 401-feature input with 96 output classes. Use 6 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-3170\nComponents:\n - input (input) params={\"shape\":[1,401]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,401]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":401,\"outFeatures\":810}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":810,\"outFeatures\":189}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":189,\"outFeatures\":314}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":314,\"outFeatures\":233}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":233,\"outFeatures\":462}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc6\",\"params\":{\"inFeatures\":462,\"outFeatures\":825}},{\"componentType\":\"relu\",\"name\":\"act6\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":825,\"outFeatures\":96}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"fc6\"},{\"from\":\"fc6\",\"to\":\"act6\"},{\"from\":\"act6\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 372-dim input: encode down to a 230-dim bottleneck and decode back to 372. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-3171\nComponents:\n - input (input) params={\"shape\":[1,372]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,372]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":372,\"outFeatures\":102}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":102,\"outFeatures\":230}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":230,\"outFeatures\":102}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":102,\"outFeatures\":372}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x57x57 image with 48 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-3172\nComponents:\n - input (input) params={\"shape\":[1,3,57,57]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,57,57]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":33,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":33,\"outChannels\":42,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":42,\"outFeatures\":48}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 183-token sequences with 87 output classes. Token embedding, 1 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-3173\nComponents:\n - input (input) params={\"shape\":[1,183]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,183]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":37760,\"embeddingDim\":144}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":144,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":144,\"outFeatures\":87}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 371-token sequences with 75 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-3174\nComponents:\n - input (input) params={\"shape\":[1,371]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,371]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":17484,\"embeddingDim\":192}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":192,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[192]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":192,\"numHeads\":8,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[192]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":192,\"outFeatures\":75}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis encoder fails validation: embedDim (458) is not divisible by numHeads (5). Repair the attention configuration in place with at most 2 actions. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-fix-3175\nComponents:\n - input (input) params={\"shape\":[1,100]}\n - embed (embedding) params={\"numEmbeddings\":49636,\"embeddingDim\":458}\n - attn (multiHeadAttention) params={\"embedDim\":458,\"numHeads\":5}\n - head (linear) params={\"inFeatures\":458,\"outFeatures\":47}\n - output (output)\nConnections:\n - input -> embed\n - embed -> attn\n - attn -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"attn\",\"params\":{\"numHeads\":2}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 3076-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-3176\nComponents:\n - input (input) params={\"shape\":[1,210]}\n - fc1 (linear) params={\"inFeatures\":210,\"outFeatures\":3076}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":3076,\"outFeatures\":3076}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":3076,\"outFeatures\":3076}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":3076,\"outFeatures\":3076}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":3076,\"outFeatures\":39}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":210,\"outFeatures\":241}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":241,\"outFeatures\":241}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":241,\"outFeatures\":241}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":241,\"outFeatures\":241}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":241,\"outFeatures\":39}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 106-feature, 40-class MLP trains unstably. Insert a batchNorm1d after each of the 3 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-3177\nComponents:\n - input (input) params={\"shape\":[1,106]}\n - fc1 (linear) params={\"inFeatures\":106,\"outFeatures\":506}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":506,\"outFeatures\":301}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":301,\"outFeatures\":176}\n - act3 (relu)\n - head (linear) params={\"inFeatures\":176,\"outFeatures\":40}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":506}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":301}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":176}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 41-feature user input and a 234-feature item input, each through its own 2-layer MLP tower ending at width 242, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-3178\nComponents:\n - user_input (input) params={\"shape\":[1,41]}\n - item_input (input) params={\"shape\":[1,234]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,41]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,234]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":41,\"outFeatures\":242}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":242,\"outFeatures\":242}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":234,\"outFeatures\":242}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":242,\"outFeatures\":242}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":484,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (33-feature input, 15 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-3179\nComponents:\n - input (input) params={\"shape\":[1,33]}\n - fc1 (linear) params={\"inFeatures\":33,\"outFeatures\":11}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":11,\"outFeatures\":11}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":11,\"outFeatures\":15}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":33,\"outFeatures\":794}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":794,\"outFeatures\":794}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":794,\"outFeatures\":15}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 121-feature input with 135 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-3180\nComponents:\n - input (input) params={\"shape\":[1,121]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,121]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":121,\"outFeatures\":443}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":443,\"outFeatures\":767}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":767,\"outFeatures\":847}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":847,\"outFeatures\":713}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":713,\"outFeatures\":344}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":344,\"outFeatures\":135}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1679-dim input: encode down to a 219-dim bottleneck and decode back to 1679. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-3181\nComponents:\n - input (input) params={\"shape\":[1,1679]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1679]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1679,\"outFeatures\":572}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":572,\"outFeatures\":219}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":219,\"outFeatures\":572}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":572,\"outFeatures\":1679}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x56x56 image with 6 classes. Use 2 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-3182\nComponents:\n - input (input) params={\"shape\":[1,3,56,56]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,56,56]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":61,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":61,\"outChannels\":48,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":48,\"outFeatures\":6}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 217-token sequences with 44 output classes. Token embedding, 3 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-3183\nComponents:\n - input (input) params={\"shape\":[1,217]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,217]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":13727,\"embeddingDim\":104}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":104,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":104,\"numHeads\":4}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn3\",\"params\":{\"embedDim\":104,\"numHeads\":4}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":104,\"outFeatures\":44}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"attn3\"},{\"from\":\"attn3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 501-token sequences with 52 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-3184\nComponents:\n - input (input) params={\"shape\":[1,501]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,501]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":34050,\"embeddingDim\":64}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":64,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[64]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":64,\"numHeads\":4,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[64]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":64,\"outFeatures\":52}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 2063-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-3186\nComponents:\n - input (input) params={\"shape\":[1,83]}\n - fc1 (linear) params={\"inFeatures\":83,\"outFeatures\":2063}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2063,\"outFeatures\":2063}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2063,\"outFeatures\":2063}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":2063,\"outFeatures\":2063}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":2063,\"outFeatures\":17}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":83,\"outFeatures\":72}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":72,\"outFeatures\":72}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":72,\"outFeatures\":72}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":72,\"outFeatures\":72}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":72,\"outFeatures\":17}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 127-feature, 87-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-3187\nComponents:\n - input (input) params={\"shape\":[1,127]}\n - fc1 (linear) params={\"inFeatures\":127,\"outFeatures\":52}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":52,\"outFeatures\":226}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":226,\"outFeatures\":495}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":495,\"outFeatures\":498}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":498,\"outFeatures\":87}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":52}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":226}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":495}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":498}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 230-feature user input and a 41-feature item input, each through its own 2-layer MLP tower ending at width 131, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-3188\nComponents:\n - user_input (input) params={\"shape\":[1,230]}\n - item_input (input) params={\"shape\":[1,41]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,230]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,41]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":230,\"outFeatures\":131}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":131,\"outFeatures\":131}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":41,\"outFeatures\":131}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":131,\"outFeatures\":131}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":262,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (51-feature input, 39 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-3189\nComponents:\n - input (input) params={\"shape\":[1,51]}\n - fc1 (linear) params={\"inFeatures\":51,\"outFeatures\":16}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":16,\"outFeatures\":16}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":16,\"outFeatures\":39}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":51,\"outFeatures\":661}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":661,\"outFeatures\":661}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":661,\"outFeatures\":39}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense classifier for a 458-feature input with 191 output classes. Use 5 hidden linear layers with ReLU and a linear head. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-mlp-3190\nComponents:\n - input (input) params={\"shape\":[1,458]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,458]}},{\"componentType\":\"linear\",\"name\":\"fc1\",\"params\":{\"inFeatures\":458,\"outFeatures\":828}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc2\",\"params\":{\"inFeatures\":828,\"outFeatures\":444}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc3\",\"params\":{\"inFeatures\":444,\"outFeatures\":396}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc4\",\"params\":{\"inFeatures\":396,\"outFeatures\":31}},{\"componentType\":\"relu\",\"name\":\"act4\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"fc5\",\"params\":{\"inFeatures\":31,\"outFeatures\":1018}},{\"componentType\":\"relu\",\"name\":\"act5\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":1018,\"outFeatures\":191}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"fc1\"},{\"from\":\"fc1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"fc2\"},{\"from\":\"fc2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"fc3\"},{\"from\":\"fc3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"fc4\"},{\"from\":\"fc4\",\"to\":\"act4\"},{\"from\":\"act4\",\"to\":\"fc5\"},{\"from\":\"fc5\",\"to\":\"act5\"},{\"from\":\"act5\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a dense autoencoder for 1914-dim input: encode down to a 151-dim bottleneck and decode back to 1914. Keep it valid and connected, under 20M params.\n\nCURRENT MODEL:\nModel: gen-ae-3191\nComponents:\n - input (input) params={\"shape\":[1,1914]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,1914]}},{\"componentType\":\"linear\",\"name\":\"enc1\",\"params\":{\"inFeatures\":1914,\"outFeatures\":805}},{\"componentType\":\"linear\",\"name\":\"enc2\",\"params\":{\"inFeatures\":805,\"outFeatures\":151}},{\"componentType\":\"linear\",\"name\":\"dec1\",\"params\":{\"inFeatures\":151,\"outFeatures\":805}},{\"componentType\":\"linear\",\"name\":\"dec2\",\"params\":{\"inFeatures\":805,\"outFeatures\":1914}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"enc1\"},{\"from\":\"enc1\",\"to\":\"enc2\"},{\"from\":\"enc2\",\"to\":\"dec1\"},{\"from\":\"dec1\",\"to\":\"dec2\"},{\"from\":\"dec2\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a convolutional classifier for a 3x49x49 image with 85 classes. Use 3 conv layers with ReLU and a linear head. Keep it under 50M params.\n\nCURRENT MODEL:\nModel: gen-cnn-3192\nComponents:\n - input (input) params={\"shape\":[1,3,49,49]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,3,49,49]}},{\"componentType\":\"conv2d\",\"name\":\"conv1\",\"params\":{\"inChannels\":3,\"outChannels\":10,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act1\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv2\",\"params\":{\"inChannels\":10,\"outChannels\":20,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act2\",\"params\":{}},{\"componentType\":\"conv2d\",\"name\":\"conv3\",\"params\":{\"inChannels\":20,\"outChannels\":28,\"kernelSize\":3}},{\"componentType\":\"relu\",\"name\":\"act3\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":28,\"outFeatures\":85}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"conv1\"},{\"from\":\"conv1\",\"to\":\"act1\"},{\"from\":\"act1\",\"to\":\"conv2\"},{\"from\":\"conv2\",\"to\":\"act2\"},{\"from\":\"act2\",\"to\":\"conv3\"},{\"from\":\"conv3\",\"to\":\"act3\"},{\"from\":\"act3\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a transformer encoder for 163-token sequences with 32 output classes. Token embedding, 2 multi-head attention block(s) with a valid head configuration, then a linear head. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-txf-3193\nComponents:\n - input (input) params={\"shape\":[1,163]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,163]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":22528,\"embeddingDim\":110}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":110,\"numHeads\":2}},{\"componentType\":\"multiHeadAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":110,\"numHeads\":2}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":110,\"outFeatures\":32}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a grouped-query-attention encoder for 154-token sequences with 59 output classes: token embedding, 2 GQA block(s) each followed by layer normalization, then a linear head. numHeads must be divisible by numKVHeads. Keep it under 60M params.\n\nCURRENT MODEL:\nModel: gen-gqa-3194\nComponents:\n - input (input) params={\"shape\":[1,154]}\n - output (output)\nConnections:\n - input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"input\",\"params\":{\"shape\":[1,154]}},{\"componentType\":\"embedding\",\"name\":\"embed\",\"params\":{\"numEmbeddings\":29913,\"embeddingDim\":656}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn1\",\"params\":{\"embedDim\":656,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm1\",\"params\":{\"normalizedShape\":[656]}},{\"componentType\":\"groupedQueryAttention\",\"name\":\"attn2\",\"params\":{\"embedDim\":656,\"numHeads\":16,\"numKVHeads\":2}},{\"componentType\":\"layerNorm\",\"name\":\"norm2\",\"params\":{\"normalizedShape\":[656]}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":656,\"outFeatures\":59}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"input\",\"to\":\"embed\"},{\"from\":\"embed\",\"to\":\"attn1\"},{\"from\":\"attn1\",\"to\":\"norm1\"},{\"from\":\"norm1\",\"to\":\"attn2\"},{\"from\":\"attn2\",\"to\":\"norm2\"},{\"from\":\"norm2\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 4-hidden-layer MLP uses 2092-wide layers and blows a 2M parameter budget. Shrink the widths in place so total params fit the budget, keeping all 4 hidden layers and consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-trim-3196\nComponents:\n - input (input) params={\"shape\":[1,230]}\n - fc1 (linear) params={\"inFeatures\":230,\"outFeatures\":2092}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":2092,\"outFeatures\":2092}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":2092,\"outFeatures\":2092}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":2092,\"outFeatures\":2092}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":2092,\"outFeatures\":29}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":230,\"outFeatures\":233}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":233,\"outFeatures\":233}},{\"type\":\"update_params\",\"name\":\"fc3\",\"params\":{\"inFeatures\":233,\"outFeatures\":233}},{\"type\":\"update_params\",\"name\":\"fc4\",\"params\":{\"inFeatures\":233,\"outFeatures\":233}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":233,\"outFeatures\":29}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 136-feature, 82-class MLP trains unstably. Insert a batchNorm1d after each of the 4 hidden linear layers (between the linear and its activation), with numFeatures matching each layer's output width. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-norm-3197\nComponents:\n - input (input) params={\"shape\":[1,136]}\n - fc1 (linear) params={\"inFeatures\":136,\"outFeatures\":340}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":340,\"outFeatures\":407}\n - act2 (relu)\n - fc3 (linear) params={\"inFeatures\":407,\"outFeatures\":450}\n - act3 (relu)\n - fc4 (linear) params={\"inFeatures\":450,\"outFeatures\":207}\n - act4 (relu)\n - head (linear) params={\"inFeatures\":207,\"outFeatures\":82}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> fc3\n - fc3 -> act3\n - act3 -> fc4\n - fc4 -> act4\n - act4 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn1\",\"afterName\":\"fc1\",\"params\":{\"numFeatures\":340}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn2\",\"afterName\":\"fc2\",\"params\":{\"numFeatures\":407}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn3\",\"afterName\":\"fc3\",\"params\":{\"numFeatures\":450}},{\"type\":\"add_component\",\"componentType\":\"batchNorm1d\",\"name\":\"bn4\",\"afterName\":\"fc4\",\"params\":{\"numFeatures\":207}}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nDesign a two-tower retrieval scorer: a 46-feature user input and a 125-feature item input, each through its own 2-layer MLP tower ending at width 375, concatenated and scored by a linear head. Both tower outputs must have identical shape for the merge. Keep it under 10M params.\n\nCURRENT MODEL:\nModel: gen-tower-3198\nComponents:\n - user_input (input) params={\"shape\":[1,46]}\n - item_input (input) params={\"shape\":[1,125]}\n - output (output)\nConnections:\n - user_input -> output\n - item_input -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"replace_model\",\"components\":[{\"componentType\":\"input\",\"name\":\"user_input\",\"params\":{\"shape\":[1,46]}},{\"componentType\":\"input\",\"name\":\"item_input\",\"params\":{\"shape\":[1,125]}},{\"componentType\":\"linear\",\"name\":\"user_fc1\",\"params\":{\"inFeatures\":46,\"outFeatures\":375}},{\"componentType\":\"relu\",\"name\":\"user_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"user_fc2\",\"params\":{\"inFeatures\":375,\"outFeatures\":375}},{\"componentType\":\"linear\",\"name\":\"item_fc1\",\"params\":{\"inFeatures\":125,\"outFeatures\":375}},{\"componentType\":\"relu\",\"name\":\"item_act\",\"params\":{}},{\"componentType\":\"linear\",\"name\":\"item_fc2\",\"params\":{\"inFeatures\":375,\"outFeatures\":375}},{\"componentType\":\"concatenate\",\"name\":\"merge\",\"params\":{\"dim\":-1}},{\"componentType\":\"linear\",\"name\":\"head\",\"params\":{\"inFeatures\":750,\"outFeatures\":1}},{\"componentType\":\"output\",\"name\":\"output\",\"params\":{}}],\"connections\":[{\"from\":\"user_input\",\"to\":\"user_fc1\"},{\"from\":\"user_fc1\",\"to\":\"user_act\"},{\"from\":\"user_act\",\"to\":\"user_fc2\"},{\"from\":\"item_input\",\"to\":\"item_fc1\"},{\"from\":\"item_fc1\",\"to\":\"item_act\"},{\"from\":\"item_act\",\"to\":\"item_fc2\"},{\"from\":\"user_fc2\",\"to\":\"merge\"},{\"from\":\"item_fc2\",\"to\":\"merge\"},{\"from\":\"merge\",\"to\":\"head\"},{\"from\":\"head\",\"to\":\"output\"}]}]}"}]} {"messages":[{"role":"system","content":"You are a neural-architecture design agent. You edit a structured model graph by emitting actions.\nRespond with ONE JSON object and nothing else: { \"actions\": [ ... ] }\n\nAction types:\n- { \"type\": \"add_component\", \"componentType\": \"\", \"name\": \"\", \"afterName\": \"\", \"params\": { ... } }\n- { \"type\": \"add_connection\", \"fromName\": \"\", \"toName\": \"\" }\n- { \"type\": \"update_params\", \"name\": \"\", \"params\": { ... } }\n- { \"type\": \"scale_params\", \"paramKey\": \"\", \"factor\": , \"namePattern\": \"\" }\n- { \"type\": \"delete_component\", \"name\": \"\" }\n- { \"type\": \"replace_model\", \"components\": [ { \"componentType\": \"...\", \"name\": \"...\", \"params\": {...} } ], \"connections\": [ { \"from\": \"...\", \"to\": \"...\" } ] }\n\nRules:\n- Insert layers in order using afterName so the graph stays connected input->output.\n- Attention: embedDim MUST be divisible by numHeads.\n- Param keys: linear {inFeatures,outFeatures}; conv2d {inChannels,outChannels,kernelSize}; embedding {numEmbeddings,embeddingDim}; multiHeadAttention {embedDim,numHeads}; groupedQueryAttention {embedDim,numHeads,numKVHeads}; transformerBlock {hiddenDim,numHeads}; batchNorm1d {numFeatures}; layerNorm {normalizedShape}; concatenate {dim}.\n- GQA: numHeads MUST also be divisible by numKVHeads.\n- If the spec says to repair or edit in place, use surgical actions (update_params, add_component); do NOT use replace_model or clear_canvas.\n- Every numeric value MUST be a single computed integer, never an arithmetic expression: write \"inFeatures\": 6400, NOT \"inFeatures\": 64 * 10 * 10.\n- Respect any parameter budget in the spec. Output only the JSON object."},{"role":"user","content":"SPEC:\nThis 2-hidden-layer MLP (22-feature input, 7 classes) is far too small for its workload. Widen the hidden layers in place so total params land between 400k and 4M, keeping consistent in/out features. Do not rebuild the model from scratch.\n\nCURRENT MODEL:\nModel: gen-grow-3199\nComponents:\n - input (input) params={\"shape\":[1,22]}\n - fc1 (linear) params={\"inFeatures\":22,\"outFeatures\":22}\n - act1 (relu)\n - fc2 (linear) params={\"inFeatures\":22,\"outFeatures\":22}\n - act2 (relu)\n - head (linear) params={\"inFeatures\":22,\"outFeatures\":7}\n - output (output)\nConnections:\n - input -> fc1\n - fc1 -> act1\n - act1 -> fc2\n - fc2 -> act2\n - act2 -> head\n - head -> output\n\nReturn the actions that fulfil the spec."},{"role":"assistant","content":"{\"actions\":[{\"type\":\"update_params\",\"name\":\"fc1\",\"params\":{\"inFeatures\":22,\"outFeatures\":699}},{\"type\":\"update_params\",\"name\":\"fc2\",\"params\":{\"inFeatures\":699,\"outFeatures\":699}},{\"type\":\"update_params\",\"name\":\"head\",\"params\":{\"inFeatures\":699,\"outFeatures\":7}}]}"}]}